Paper Digest: Recent Papers on Anomaly Detection

October 13, 2020May 18, 2026 admin

Paper Digest Team extracted all recent Anomaly Detection related papers on our radar, and generated highlight sentences for them. The results are then sorted by relevance & date. In addition to this ‘static’ page, we also provide a real-time version of this article, which has more coverage and is updated in real time to include the most recent updates on this topic.

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Paper Digest Team
New York City, New York, 10017
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TABLE 1: Paper Digest: Recent Papers on Anomaly Detection

	Paper	Author(s)	Source	Date
1	Dynamic Graph with Knowledge Graph Embeddings for Blockchain Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yuzhi Zhu; Zeyan Li;	International Journal of Machine Learning and Cybernetics	2026-05-16
2	EnvGreenAE: A Denoising-enhanced Transformer Autoencoder for Greenhouse Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Guoyi Wang; Weijun Yang; Xiji Hu; Xinxing Li; Buwen Liang;	Computers and Electronics in Agriculture	2026-05-16
3	Matrix Profile for Anomaly Detection in Hyperspectral Images: Application to The Early Detection of Apple Scab Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Meryem Amrani Idrissi; Reza Akbarinia; Florent Masseglia; Matthieu Lesnoff; Jean-Michel Roger;	Chemometrics and Intelligent Laboratory Systems	2026-05-15
4	Self-Supervised Log Anomaly Detection with LogBERT-Style Transformers: Full Empirical Evaluation on A Reproducible SynHDFS Benchmark Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a LogBERT-style transformer framework for session-level log anomaly detection and reports a complete, reproducible experimental evaluation.	Qi Xin;	JEECS (Journal of Electrical Engineering and Computer …	2026-05-14
5	Tri-modal Video Anomaly Detection Via Hierarchical Contrastive Calibration Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Maowen Zhou; Erma Rahayu Mohd Faizal Abdullah; Aznul Qalid Md Sabri; Susanto Rahardja;	Array	2026-05-14
6	Deep-learning Time-series Anomaly Detection of Acute Kidney Injury from Creatinine–eGFR Trajectories in The ICU Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We compared scores across Kidney Disease: Improving Global Outcomes (KDIGO) stages and evaluated 24–96-hour KRT and mortality using area under the receiver operating characteristic curve (AUROC), accuracy, and F1-score.	YOONJIN KANG et. al.	PLOS Digital Health	2026-05-13
7	Conformal Anomaly Detection in Python: Moving Beyond Heuristic Thresholds with ‘nonconform’ Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present ‘nonconform’, a Python package for applying conformal anomaly detection within existing machine-learning workflows, and use it as the basis for an implementation-grounded introduction to the field.	Oliver Hennhöfer; Maximilian Kirsch; Christine Preisach;	arxiv-stat.ML	2026-05-13
8	Deep-learning Time-series Anomaly Detection of Acute Kidney Injury from Creatinine-eGFR Trajectories in The ICU Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We compared scores across Kidney Disease: Improving Global Outcomes (KDIGO) stages and evaluated 24-96-hour KRT and mortality using area under the receiver operating characteristic curve (AUROC), accuracy, and F1-score.	YOONJIN KANG et. al.	PLOS digital health	2026-05-13
9	EEG Anomaly Detection Using XGBoost and ConvLSTM Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Wenjuan Wu; Jiafei Dai; Mohsin Hasan; Xudong Gu;	Annals of Operations Research	2026-05-12
10	Anomaly-aware Prompt Learning and Multi-scale Feature Adaptation for Zero-shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	ZHIXING LI et. al.	Journal of King Saud University Computer and Information …	2026-05-12
11	Conditional Anomaly Detection Methods for Patient-management Alert Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The work presented in this paper focuses on instance-based methods for detecting conditional anomalies.	MICHAL VALKO et. al.	arxiv-cs.LG	2026-05-11
12	MMVIAD: Multi-view Multi-task Video Understanding for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce MMVIAD (Multi-view Multi-task Video Industrial Anomaly Detection), to the best of our knowledge the first continuous multi-view video dataset for industrial anomaly detection and understanding, together with a benchmark for multi-task evaluation.	XIRAN ZHAO et. al.	arxiv-cs.CV	2026-05-11
13	FedCIGAR: A Personalized Reconstruction Approach for Federated Graph-level Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing methods suffer from poor generalization due to the reliance on unrealistic synthetic anomalies and insufficient personalization capabilities under data heterogeneity. To address these challenges, we propose a novel Federated graph-level anomaly detection approach with Cluster-adaptIve GAted Reconstruction (FedCIGAR).	YUNFENG ZHAO et. al.	arxiv-cs.LG	2026-05-10
14	Seeing The Needle in The Haystack: Towards Weakly-Supervised Log Instance Anomaly Localization Via Counterfactual Perturbation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, in networked systems at scale, log data are generated at massive scale while instance-level annotations are prohibitively expensive, posing great difficulties to fine-grained anomaly localization. To address this challenge, we propose LogMILP (Log anomaly localization based on Multi-Instance Learning enhanced by prototypes and Perturbation), a weakly supervised framework that enables both bag-level anomaly detection and instance-level anomaly localization using only bag-level labels.	Yutszyuk Wong; Wentai Wu; Yuen-Ying Yeung; Weiwei Lin;	arxiv-cs.LG	2026-05-09
15	Privacy-Aware Video Anomaly Detection Through Orthogonal Subspace Projection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose the Orthogonal Projection Layer (OPL), a lightweight module that removes task-irrelevant variations to produce representations focused on anomaly-relevant cues.	Lei Wang; Wenxiang Diao; Andrew Busch; Jun Zhou; Yongsheng Gao;	arxiv-cs.CV	2026-05-08
16	Improving The Reliability of UAV-Based Crack Inspection of Port Quay Walls Using Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The proposed method introduces anomaly detection after object detection so that detected crack candidate regions are re-evaluated based on their deviation from the learned feature distribution of crack images.	Masachika Akage; Daisuke Yoshida; Wakana Fujimoto;	Geomatics	2026-05-07
17	Detecting Time Series Anomalies Like An Expert: A Multi-Agent LLM Framework with Specialized Analyzers Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose SAGE (Specialized Analyzer Group for Expert-like Detection), a multi-agent framework for structured anomaly diagnosis in univariate time series.	Hyeongwon Kang; Jeongseob Kim; Jinwoo Park; Pilsung Kang;	arxiv-cs.AI	2026-05-07
18	Evidence-based Anomaly Detection in Clinical Domains Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we develop and examine new probabilistic anomaly detection methods that let us evaluate management decisions for a specific patient and identify those decisions that are highly unusual with respect to patients with the same or similar condition.	Milos Hauskrecht; Michal Valko; Branislav Kveton; Shyam Visweswaran; Gregory Cooper;	arxiv-cs.LG	2026-05-06
19	Two Steps Are All You Need: Efficient 3D Point Cloud Anomaly Detection with Consistency Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Existing methods are often computationally prohibitive or unreliable in complex, unmasked regions, and diffusion pipelines are inherently bottlenecked by iterative denoising. In this work, we address this bottleneck by reformulating reconstructionbased anomaly detection through consistency learning, enabling direct prediction of anomaly-free geometry in one or two network evaluations.	PRANAV A et. al.	arxiv-cs.CV	2026-05-06
20	The Clinical Significance of Imaging Biomarkers Discoverable By Anomaly Detection Methods in Retinal Diseases: A Review Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Moreover, when integrated into clinical workflows, they have the potential to enhance practical applicability by supporting efficient screening, longitudinal disease monitoring, and objective assessment of treatment response. This review examines the role of anomaly detection for discovering clinically relevant retinal imaging biomarkers, by categorizing biomarkers according to their underlying pathophysiology, summarizing the spectrum of anomaly detection methods applied in the field, and highlighting biomarkers that have been identified through these approaches.	ANNA M WITTMANN et. al.	Journal of ophthalmology	2026-05-05
21	Cluster-Aware Causal Mixer for Online Anomaly Detection in Multivariate Time Series Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: In addition, anomaly scoring methods that ignore temporal continuity can mislead sequential detection. To address these challenges, we propose a cluster-aware causal mixer for multivariate time-series anomaly detection.	Mahmuddun Murad; Yasin Yilmaz;	icml	2026-05-05
22	Normality Calibration in Semi-supervised Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, the normality learned by existing semi-supervised GAD methods is limited to the labeled normal nodes, often inclining to overfitting the given patterns, thereby leading to high detection errors, such as high false positives. To overcome this limitation, we propose $GraphNC$, a graph normality calibration framework that leverages both labeled and unlabeled data to calibrate the normality from a teacher (a pre-trained semi-supervised GAD model) jointly in anomaly score and representation spaces.	Guolei Zeng; Hezhe Qiao; GUOGUO AI; Jinsong Guo; Guansong Pang;	icml	2026-05-05
23	TD-VAD: Breaking Visual Dependence in Video Anomaly Detection with Text-Driven Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we advocate that the effectiveness of treating texts as video sequences for the VAD model and propose a novel Text-Driven Video Anomaly Detection (TD-VAD) approach to break visual dependence.	SHUANGQING ZHANG et. al.	icml	2026-05-05
24	Noise-Robust Density Estimation for Tabular Data Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Density-based anomaly detection methods often provide accurate and interpretable predictions but their performance can be severely degraded by the inherent noise of data, such as changes arising from environmental conditions during data collection or background noise. To deal with such noise, we present noise-robust density estimation (NRDE) for tabular data anomaly detection.	Dazhi Fu; Zhao Zhang; Jicong Fan;	icml	2026-05-05
25	Towards One-for-All Anomaly Detection for Tabular Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing methods follow a “one model for one dataset (OFO)” paradigm, which relies on dataset-specific training and thus incurs high computational cost and yields limited generalization to unseen domains. To address these limitations, we propose OFA-TAD, a generalist one-for-all (OFA) TAD framework that only requires one-time training on multiple source datasets and can generalize to unseen datasets from diverse domains on-the-fly.	SHIYUAN LI et. al.	icml	2026-05-05
26	Is Training Necessary for Anomaly Detection? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We then abandon the reconstruction paradigm entirely and propose Retrieval-based Anomaly Detection (RAD).	Xingwu Zhang; Guanxuan Li; Paul Henderson; Gerardo Aragon-Camarasa; ZIJUN LONG;	icml	2026-05-05
27	Anomaly-Aware Association Discrepancy for Temporal Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we emphasize an intuitive but important characteristic of the association distribution of anomalous points, which is that anomalous points show an extreme distribution while normal ones show a uniform distribution.	F. Li; X. He; J. Wang; X. Zhao;	icassp	2026-05-04
28	Robust Hyperspectral Anomaly Detection Via Constrained Difference-of-Convex Optimization Under Mixed Noise Contamination Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In addition, the anomaly component is often modeled with ℓ1-type norms, whose convex nature limits their ability to rigorously enforce sparsity. To address these limitations, we propose a novel HS anomaly detection method that explicitly models mixed noise and promotes anomaly sparsity using a difference-of-convex (DC) function.	K. Sato; S. Ono;	icassp	2026-05-04
29	Handling Heterogeneous Features: Modeling Continuous-Discrete Feature Interaction for Time Series Anomaly Detection Via Conditional Diffusion Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose CDDiff, a Conditional Diffusion framework for heterogeneous anomaly detection, integrating two designs: a dual-path diffusion process where an autoregressive path reconstructs continuous features and a conditional path which dynamically integrates the discrete features at each reverse step.	A. Zhang; P. Xu; C. K. Yeo;	icassp	2026-05-04
30	3D-Aware Semantic Alignment: Joint Global and Local Modeling for 3D Few-shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Recent vision–language approaches for 3D few-shot anomaly detection adopt multi-view projections of point cloud, which may underrepresent fine geometric cues. To overcome this limitation, the 3D-Aware Semantic Alignment framework (3DASA) is proposed.	M. Huang;	icassp	2026-05-04
31	Faclip : Learnable Fine-Grained Prompts and Multi-Scale Fusion for Zero-Shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Zero-Shot Anomaly Detection (ZSAD) enables detecting anomalies without defective samples and has gained increasing attention, current methods based on Vision-Language Models (VLM) like CLIP demonstrates limited sensitivity to fine-grained anomalies, and its prompt templates exhibit constraints when dealing with specific anomaly types. To address these challenges, we propose a novel ZSAD framework called FACLIP, it eliminates the need for fixed text prompts by incorporating learnable anomaly prompts generated with the help of large language models, and it employs a cross-modal multi-scale attention fusion module to integrate multi-scale local visual features across modalities.	S. ZHAO et. al.	icassp	2026-05-04
32	HoTGAD: High-Order and Temporal Pattern Reconstruction for Dynamic Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Anomaly camouflage, on the other hand, describes the phenomenon where anomalous nodes strategically connect to well-behaved neighbors, making them harder to identify. To bridge this gap, this paper proposes HoTGAD, a novel framework for dynamic graph anomaly detection.	D. Guo; Y. Shi; T. Huang; Y. Wang; J. Gao;	icassp	2026-05-04
33	Wavelet-Aware Anomaly Detection in Multi-Channel User Logs Via Deviation Modulation and Resolution-Adaptive Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: These logs are often multi-channel, non-stationary, and anomalies are rare, making anomaly detection challenging. To address these issues, we propose a novel framework that integrates wavelet-aware modulation, multi-resolution wavelet decomposition, and resolution-adaptive attention for robust anomaly detection.	K. Kong; D. Liu; X. Jin; S. Xu; G. Geng;	icassp	2026-05-04
34	From Silent Flows to Speaking Guardians: LLM-Enhanced Framework for IoT Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents FlowGuard, an LLM-enhanced framework for graph-based IoT network anomaly detection.	H. Ding;	icassp	2026-05-04
35	C&F-WSVAD: Towards High-Performance Coarse and Fine-Grained Weakly-Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes C&F-WSVAD, a novel method leveraging video-text multimodal data and multiscale temporal dependencies to overcome WSVAD limitations.	Y. Wang; J. Zhou; J. Guan; S. Zhou;	icassp	2026-05-04
36	One-Stage Semi-Supervised Semantic Segmentation for Anomaly Detection Via Consistency Regularization and Student-Teacher Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose SSAD (Semi-Supervised Semantic Segmentation-based Anomaly Detection), which incorporates segmentation techniques more suitable for the SSS scenario.	Y. Nakanishi;	icassp	2026-05-04
37	Robust Unsupervised Set-Level Anomaly Detection for Small Test-Time Sets Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a method based on a PoolModel autoencoder, introducing an outputset oversampling (enlarging the decoder’s output set) to reduce score variance for small sets.	R. Nakai;	icassp	2026-05-04
38	Contextual Clue Mining and Class Calibration for Weakly Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Additionally, for multi-category anomaly classification, CLIP’s compact normal-class embedding potentially leads to inter-class confusion, causing misclassification of normal frames. To address these challenges, we propose the Contextual Clue Mining network for Weakly Supervised Video Anomaly Detection (C2M-VAD), a novel WS-VAD framework integrating two key components: a temporal selective kernel module that adaptively adjusts the receptive field via input-conditioned kernel fusion, and an anomaly-class calibration module that mitigates semantic confusion through residual correction of CLIP logits.	S. Zhang;	icassp	2026-05-04
39	Efficient3D-AD: Token-Efficient and View-Aware Zero-shot 3D Multimodal Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, rendering many views increases computational cost, and redundant views can introduce uninformative or misleading features that reduce detection accuracy. To address these challenges, we propose an efficient zero-shot 3D anomaly detection framework with two key components.	J. Chen; L. Gu; X. Chen; Z. Li;	icassp	2026-05-04
40	AD-DINOv3: Enhancing DINOv3 for Zero-Shot Anomaly Detection with Anomaly-Aware Calibration Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To address them, we introduce lightweight adapters for vision and text modalities to recalibrate features, and propose an Anomaly-Aware Calibration Module (AACM) that enhances CLS–patch interaction for anomaly-focused Image DINOv3 Ours representations.	J. Yuan; J. Ye; W. Chen; C. Gao;	icassp	2026-05-04
41	Traffic Anomaly Detection Via Dimension-Aware Multi-View Alignment Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: With growing volumes of anomaly traffic and increasingly stealthy attack types, anomaly detection becomes more challenging due to unclear inter-class boundaries and imbalanced intra-class characteristics. To address these issues, we propose DAMA, an effective network traffic anomaly detection framework based on Dimension-Aware Multi-view Alignment.	H. Yu;	icassp	2026-05-04
42	Cross Pseudo Labeling for Weakly Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose CPL-VAD, a dual-branch framework with cross pseudo labeling.	D. Lee; D. Kim; C. Park; S. Woo; S. Lee;	icassp	2026-05-04
43	Boosting Anomaly Detection in Industrial 3D Data: An Entropy-Guided Denoising Autoencoder Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Reconstruction-based methods excel in efficient training and direct error-based scoring; however, they face limitations like suboptimal masking strategies, inadequate semantic recovery, and poor performance in high-precision scenarios. To address these challenges, we introduce an Entropy-Guided Denoising Autoencoder (Eng-DAE), a novel reconstruction-based framework that integrates masked and denoising autoencoders for efficient and robust anomaly detection.	Z. Chen; Y. Zhang; B. Chen;	icassp	2026-05-04
44	Video Quality Anomaly Detection Based on Multimodal Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Traditional video quality assessment (VQA) methods primarily predict global quality scores but fall short in identifying and classifying fine-grained anomalies across spatial and temporal dimensions. To address this limitation, we present VQAD-15, a large-scale instruction-following dataset tailored for Video Quality Anomaly Detection.	Z. Liu;	icassp	2026-05-04
45	Toward Faithful Explanations in Acoustic Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we study the interpretability of autoencoder-based models for audio anomaly detection, by comparing a standard autoencoder (AE) with a mask autoencoder (MAE) in terms of detection performance and interpretability.	M. ELRASHID et. al.	icassp	2026-05-04
46	Deep Supervised Anomaly Detection for Generalized Face Forgery Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	FAN ZHANG et. al.	Pattern Recognit.
47	Retrieval-augmented Generation Enhanced LLM for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yifu Chen;	Discover Applied Sciences	2026-05-02
48	Distance Metric Learning for Conditional Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The work presented in this paper focuses on instance-based methods for detecting conditional anomalies.	Michal Valko; Milos Hauskrecht;	arxiv-cs.LG	2026-05-01
49	Dual-Masked and Discriminative Reconstruction for Unified Vision Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Unsupervised reconstruction networks have shown promise for unified vision anomaly detection, i.e., image-level anomaly classification and pixel-level anomaly segmentation, where a single model trained on multi-class normal images can detect various anomalies.	Bin-Bin Gao;	IEEE transactions on image processing : a publication of …	2026-05-01
50	EventADL: Open-Box Anomaly Detection and Localization Framework for Events in Cloud-Based Service Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Recent ADL developments focus on metric and log data, leaving event data unexplored. To address this gap, we propose EventADL, the first open-box event-based ADL framework for cloud-based service systems.	Luan Pham; Victor Nicolet; Joey Dodds; Hui Guan; Daniel Kroening;	arxiv-cs.LG	2026-04-30
51	Neuromorphic Graph Anomaly Detection Via Adaptive STDP and Spiking Graph Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces ASTDP-GAD, a novel Adaptive Spiking Temporal Dynamics Plasticity framework for Graph Anomaly Detection that integrates spiking graph neural networks with STDP learning for energy-efficient neuromorphic detection in dynamic networks.	Abdul Joseph Fofanah; Lian Wen; David Chen; Tsungcheng Yao; Kwabena Sarpong;	arxiv-cs.NE	2026-04-29
52	Real-Time Self-Evolving Intelligence System with LLM Integration for Multi-Tenant Invoice Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a self-evolving, schema-adaptive anomaly detection system designed specifically for multi-tenant billing and invoicing environments.	Aniket Kumar Aniket Kumar; Pawan Kumar Pawan Kumar; Eklavya Singh Eklavya Singh;	International Journal of Creative and Open Research in …	2026-04-29
53	Vision to Detection: Physics-informed Data Augmentation and Relevance-weighted Random Forests for Electromagnetic Needle Selection Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Laihu Peng; Song Liu; Yubao Qi; Xin Ru; Kaiyuan Shao;	Signal, Image and Video Processing	2026-04-28
54	Unsupervised Graph Modeling for Anomaly Detection in Accounting Subject Relationships Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper addresses the problem of anomaly detection in accounting subject association structures, proposing a structured modeling and unsupervised discriminant framework based on graph neural networks.	YUHAN WANG et. al.	arxiv-cs.LG	2026-04-28
55	Complex Product Assembly Anomaly Inspection Based on Reference-view Synthesis and Cross-domain Comparison Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The proposed method achieves improvements of 5.09%, 9.86%, 9.28%, and 7.65% in Precision, Recall, F1-score, and mIoU, respectively.	Nengbin Lv; Zhangmao Xu; Shaohua Meng; Feifei Kong; Fuzhou Du;	Measurement Science and Technology	2026-04-27
56	Road Traffic Anomaly Detection By Human-Attention-Assisted Text-Vision Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the rapid development of society, the number of road vehicles has increased significantly, leading to a growing severity of traffic accident issues. Timely and accurate …	Yachuang Chai; Wushouer Silamu;	Sensors (Basel, Switzerland)	2026-04-24
57	Road Traffic Anomaly Detection By Human-Attention-Assisted Text–Vision Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Utilizing the well-known video-text model CLIP, we have constructed a detection model that leverages unique text and eye-gaze annotation data from the TADS dataset to learn anomaly representations more effectively, thereby improving the detection of road traffic anomalies from a surveillance perspective.	Yachuang Chai; Wushouer Silamu;	Sensors	2026-04-24
58	Text-Guided Multimodal Unified Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing unsupervised methods suffer from two critical limitations: ambiguous cross-modal alignment caused by the lack of high-level semantic guidance and insufficient geometric modeling for RGB-to-3D feature mapping. To address these issues, we propose a unified multimodal industrial anomaly detection framework guided by text semantics.	Zewen Li; Shuo Ye; Zitong Yu; Weicheng Xie; Linlin Shen;	arxiv-cs.CV	2026-04-24
59	Conditional Anomaly Detection Using Soft Harmonic Functions: An Application to Clinical Alerting Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we consider the problem of conditional anomaly detection that aims to identify data instances with an unusual response, such as the omission of an important lab test.	Michal Valko; Hamed Valizadegan; Branislav Kveton; Gregory F. Cooper; Milos Hauskrecht;	arxiv-cs.LG	2026-04-23
60	Conditional Anomaly Detection with Soft Harmonic Functions Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we consider the problem of conditional anomaly detection that aims to identify data instances with an unusual response or a class label.	Michal Valko; Branislav Kveton; Hamed Valizadegan; Gregory F. Cooper; Milos Hauskrecht;	arxiv-cs.LG	2026-04-23
61	Revisiting Reconstruction-based Anomaly Detection for Whole Slide Image Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, obtaining high-quality annotations remains a major bottleneck. Task-aware unsupervised anomaly detection models offer a promising alternative, as they are trained solely on task-specific normal data and can be adapted to clinically defined objectives, such as cancer detection, depending on the problem formulation.	Bin Xiao; Collins Wangulu; Theodorus van der Kwast; George M Yousef; Fatemeh Zabihollahy;	IEEE transactions on medical imaging	2026-04-23
62	ANOMALY BASED INTRUSION AND DETECTION WITH MACHINE LEARNING Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Abstract: Anomaly detection is the identification of rare events, items, or observations which are suspicious because they differ significantly from standard behaviours or …	Vani Krishnaswamy; Dr.S.P Swornambiga;	INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING …	2026-04-22
63	A Hierarchical Ensemble Pipeline for Anomaly Detection in ESA Satellite Telemetry Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: A hierarchical ensemble pipeline is introduced to address anomaly detection in multivariate telemetry data provided by European Space Agency (ESA).	Lorenzo Riccardo Allegrini; Geremia Pompei;	arxiv-cs.LG	2026-04-22
64	ULEAD-TabPFN: Uncertainty-aware Dependency-based Anomaly Detection with TabPFN Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing methods often struggle to model such dependencies robustly and to scale to high-dimensional data with complex dependency structures. To address these challenges, we propose uLEAD-TabPFN, a dependency-based anomaly detection framework built on Prior-Data Fitted Networks (PFNs).	SHA LU et. al.	arxiv-cs.LG	2026-04-22
65	LayoutAD: Exploring Semantic-Geometric Misalignment Reasoning for Scene Layout Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: These overlooked layout anomalies remain critical yet underexplored, e.g., factually defective hallucinations appeared in generative text-to-image models. Based on the above observation, in this paper, we introduce scene layout anomaly detection, a new task that predicts an object-level anomaly map from the input image to reveal the semantic plausibility and geometric consistency of each object in the scene.	Zhichao Zeng; Jiasheng Zhang; Jiyun Sun; Jiangtao Cui; Xiaotian Qiao;	cvpr	2026-04-21
66	MMR-AD: A Large-Scale Multimodal Dataset for Benchmarking General Anomaly Detection with Multimodal Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To facilitate MLLM-based general AD research, we present MMR-AD, which is a comprehensive benchmark for both training and evaluating MLLM-based AD models.	Xincheng Yao; Zefeng Qian; Chao Shi; Jiayang Song; Chongyang Zhang;	cvpr	2026-04-21
67	VisualAD: Language-Free Zero-Shot Anomaly Detection Via Vision Transformer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work revisits the necessity of the text branch in ZSAD and presents VisualAD, a purely visual framework built on Vision Transformers.	YANNING HOU et. al.	cvpr	2026-04-21
68	Back to Point: Exploring Point-Language Models for Zero-Shot 3D Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we revisit intrinsic 3D representations and explore the potential of pre-trained Point-Language Models (PLMs) for ZS 3D anomaly detection.	KAIQIANG LI et. al.	cvpr	2026-04-21
69	Geometry-Aligned and Anomaly-Aware Reconstruction for 3D Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, these approaches still face two major challenges: (1) geometry violation, where random noise perturbations deviate from local surface normals, causing structural distortion; and (2) undistinguished reference regions, where uniformly applied coarse anomaly embeddings during denoising blur normal details and impede accurate anomaly recovery. To address these issues, we propose AARD, a geometry-aligned and anomaly-aware diffusion reconstruction framework.	linchun wu; Qin Zou; Yuanhao Yue; Zhongyuan Wang;	cvpr	2026-04-21
70	Weakly Supervised Video Anomaly Detection with Anomaly-Connected Components and Intention Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, a key limitation persists in WS-VAD, as dense frame-level annotations are absent, which often leaves existing methods struggling to learn anomaly semantics effectively. To address this issue, we propose a novel framework named LAS-VAD, short for \textbf{L}earning \textbf{A}nomaly \textbf{S}emantics for WS-\textbf{VAD}, which integrates anomaly-connected component mechanism and intention awareness mechanism.	Yu Wang; Hongli Liu;	cvpr	2026-04-21
71	No Need For Real Anomaly: MLLM Empowered Zero-Shot Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Key contributing factors include limited dataset diversity, and inadequate understanding of context-dependent anomalous semantics. To address these issues, i) we propose LAVIDA, an end-to-end zero-shot video anomaly detection framework.	Zunkai Dai; Ke Li; JIAJIA LIU; Jie Yang; Yuanyuan Qiao;	cvpr	2026-04-21
72	One-to-More: High-Fidelity Training-Free Anomaly Generation with Attention Control Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Although numerous few-shot anomaly synthesis methods have been proposed to augment anomalous data for downstream AD tasks, most existing approaches require time-consuming training and struggle to learn distributions that are faithful to real anomalies, thereby restricting the efficacy of AD models trained on such data. To address these limitations, we propose a training-free few-shot anomaly generation method, namely O2MAG, which leverages the self-attention in One reference anomalous image to synthesize More realistic anomalies, supporting effective downstream anomaly detection.	HAOXIANG RAO et. al.	cvpr	2026-04-21
73	Real-Time Anomaly Detection System (RADS): A Lightweight, Database-Free Approach for System Performance and Security Monitoring Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes a Real-Time Anomaly Detection System (RADS), a lightweight and database-free framework designed for instant detection of abnormal system behavior.	Shakila Siddavatam; Nagma Khan;	INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING …	2026-04-21
74	Reasoning-Driven Anomaly Detection and Localization with Image-Level Supervision Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we activate the intrinsic reasoning potential of MLLMs to perform anomaly detection, pixel-level localization, and interpretable reasoning solely from image-level supervision, without any auxiliary components or pixel-wise labels.	YIZHOU JIN et. al.	cvpr	2026-04-21
75	Cost-effective Anomaly Detection with Active Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Sohee Bae; Jaewoong Shim;	Computers & Industrial Engineering	2026-04-21
76	ADSeeker: A Knowledge-Grounded Reasoning Framework for Industry Anomaly Detection and Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: SEEK-M\&V includes semantic-rich descriptions and image-document pairs, enabling more comprehensive anomaly understanding. To effectively retrieve and utilize this knowledge, we introduce the Query Image-Knowledge Retrieval-Augmented Generation (Q2K RAG) framework.	KAI ZHANG et. al.	cvpr	2026-04-21
77	A Semantically Disentangled Unified Model for Multi-category 3D Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: While a unified model improves scalability by learning across multiple categories, it often suffers from Inter-Category Entanglement (ICE)—where latent features from different categories overlap, causing the model to adopt incorrect semantic priors during reconstruction and ultimately yielding unreliable anomaly scores. To address this issue, we propose the Semantically Disentangled Unified Model for 3D Anomaly Detection, which reconstructs features conditioned on disentangled semantic representations.	SuYeon Kim; Wongyu Lee; MyeongAh Cho;	cvpr	2026-04-21
78	Defect Cue-Preserved Structural Feature Refinement for Few-Shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To counteract the defect cue fading, we propose a Defect Cue-Preserved Structural Feature Refinement model, referred to as DCP-SFR.	LE JIANG et. al.	cvpr	2026-04-21
79	Wavelet-Driven 3D Anomaly Detection Under Pose-Agnostic and Sparse-View Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, under sparse-view conditions, existing methods face two key challenges: (1) sparse observations lead to overfitting and geometric detail loss in 3D reconstruction; (2) limited visual cues lead to inaccurate pose estimation, compromising the reliability of subsequent anomaly localization. To address these challenges, we propose Wave-Pose3D, a wavelet-driven 3D anomaly detection framework tailored for PAD under sparse-view conditions.	MINGWEN SHAO et. al.	cvpr	2026-04-21
80	ZSG-IAD: A Multimodal Framework for Zero-Shot Grounded Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose ZSG-IAD, a multimodal vision-language framework for zero-shot grounded industrial anomaly detection.	Qiuhui Chen; Jiaxiang Song; Shuai Tan; Weimin Zhong;	arxiv-cs.CV	2026-04-20
81	Enhancing Tabular Anomaly Detection Via Pseudo-Label-Guided Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, unsupervised methods lack sufficient anomaly awareness, while current generation and contrastive approaches tend to compute anomalies globally, overlooking the localized anomaly patterns of tabular features, resulting in suboptimal detection performance. To address these limitations, we propose PLAG, a pseudo-label-guided anomaly generation method designed to enhance tabular anomaly detection.	WEI HUANG et. al.	arxiv-cs.AI	2026-04-20
82	Automatic Deep Anomaly Detection Using Thermograpy Based Convolution Autoencoder Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Save	NAGA PRASANTHI YERNENI et. al.	Journal of Nondestructive Evaluation	2026-04-17
83	Hybrid Supervised Learning for Enhanced Open-world Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Weijie Gao; Jiaxu Leng; Xiangqi Meng; Changhe Tu;	The Visual Computer	2026-04-16
84	Anomaly Detection in Financial Transactions Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This research paper presents a comprehensive review and comparative analysis of machine learning techniques applied to anomaly detection in financial transactions, with a focus on their effectiveness, scalability, and real-world applicability.	Prof. Mohammad Asif; Vrajkumar Patel; Prof. Dr. Vikram Kumar; Hemil Prajapati;	International Scientific Journal of Engineering and …	2026-04-16
85	Looking at Anomaly Detection in EdgeAI Through The Up-to-date Lens of Academic and Market Perspectives Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this way, the present survey aims to investigate the main concerns of anomaly detection, addressing the opportunity outlined above.	ALBERTH DOS SANTOS OLIVEIRA et. al.	Cluster Computing	2026-04-15
86	ASTER: Latent Pseudo-Anomaly Generation for Unsupervised Time-Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose ASTER, a framework that generates pseudo-anomalies directly in the latent space, avoiding handcrafted anomaly injections and the need for domain expertise.	Romain Hermary; Samet Hicsonmez; Dan Pineau; Abd El Rahman Shabayek; Djamila Aouada;	arxiv-cs.LG	2026-04-15
87	Unsupervised Domain Adaptation for Visual Anomaly Detection in Nondestructive Evaluation Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Hien Vu Pham; Phan Xuan Tan; Minhhuy Le; Ngoc-Tam Bui;	Journal of Nondestructive Evaluation	2026-04-15
88	Fun-TSG: A Function-Driven Multivariate Time Series Generator with Variable-Level Anomaly Labeling Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: These shortcomings hinder the development and rigorous comparison of detection models, especially those targeting interpretable and variable-specific outputs. To address this gap, we introduce Fun-TSG, a fully customizable time series generator designed to support high-quality evaluation of anomaly detection systems.	Pierre Lotte; André Péninou; Olivier Teste;	arxiv-cs.AI	2026-04-14
89	Out of Context: Reliability in Multimodal Anomaly Detection Requires Contextual Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This perspective has implications for model design, evaluation protocols, and benchmark construction, and outline open research challenges toward robust, context-aware multimodal anomaly detection.	KEVIN WILKINGHOFF et. al.	arxiv-cs.LG	2026-04-14
90	Behavioral Anomaly Detection for IoT Devices Using Lightweight Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes a lightweight anomaly detection framework designed for edge deployment using a Raspberry Pi.	Dr. Suneetha Mulumudi; Varun Juluru; Morarji Thorne; Subhadra Tejavath; Sowmya Macharla;	Research Digest on Engineering Management and Social …	2026-04-13
91	Trajectory Anomaly Detection Via Spatial–temporal Complementary Reconstruction Diffusion Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save	WEIMING XU et. al.	GeoInformatica	2026-04-13
92	Toward Human-Centered Explainability: Natural Language Explanations for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Héctor Padín-Torrente; Victor Carneiro-Diaz; Ines Ortega-Fernandez;	Information Systems Frontiers	2026-04-10
93	CAD 100K: A Comprehensive Multi-Task Dataset for Car Related Visual Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing methods remain task-specific, hindered by the absence of a unified benchmark for multi-task evaluation. To fill in this gap, We present the CAD Dataset, a large-scale and comprehensive benchmark designed for car-related multi-task visual anomaly detection.	JIAHUA PANG et. al.	arxiv-cs.CV	2026-04-10
94	Parameter-efficient Contrastive Language-image Pre-training (CLIP) Adaptation for Few-shot Anomaly Detection in Ultra-widefield Fundus Images Related Papers Related Patents Related Grants Related Venues Related Experts View Save	GUOLIANG LIAO et. al.	Photodiagnosis and photodynamic therapy	2026-04-09
95	A Hybrid Machine Learning Framework for Real-Time Anomaly Detection and Cyberattack Mitigation in Industrial Environment Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a result-oriented analysis of a deep learning-based unsupervised anomaly detection framework utilizing a Stacked Autoencoder (SAE).	Anjali Choudhary; Abhishek Sharma; Gaurav Kumar Das;	INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING …	2026-04-09
96	Mitigating The Reconstruction-detection Trade-off in VAE-based Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we reveal a trade-off between reconstruction quality and anomaly detection among $β$-VAE models.	Agathe Senellart; Maëlys Solal; Stéphanie Allassonnière; Ninon Burgos;	arxiv-cs.LG	2026-04-09
97	Distributional Reservoir State Analysis for Real-time Anomaly Detection in Multivariate Time Series Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing sliding window-based methods often suffer from delayed detection, and deep learning techniques impose training inefficiencies. To address these challenges, we propose the Mahalanobis Distance of Reservoir States (MD-RS) method.	Hiroto Tamura; Kantaro Fujiwara; Kazuyuki Aihara; Gouhei Tanaka;	npj Artificial Intelligence	2026-04-08
98	SGANet: Semantic and Geometric Alignment for Multimodal Multi-view Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing unsupervised methods often suffer from feature inconsistency arising from viewpoint variations and modality discrepancies. To address these challenges, we propose a Semantic and Geometric Alignment Network (SGANet), a unified framework for multimodal multi-view anomaly detection that effectively combines semantic and geometric alignment to learn physically coherent feature representations across viewpoints and modalities.	Letian Bai; Chengyu Tao; Juan Du;	arxiv-cs.CV	2026-04-07
99	SMT-AD: A Scalable Quantum-inspired Anomaly Detection Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Here, we propose a highly parallelizable quantum-inspired approach which we call SMT-AD from Superposition of Multiresolution Tensors for Anomaly Detection.	APIMUK SORNSAENG et. al.	arxiv-cs.LG	2026-04-06
100	InCTRLv2: Generalist Residual Models for Few-Shot Anomaly Detection and Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To this end, this work introduces InCTRLv2, a novel few-shot Generalist Anomaly Detection and Segmentation (GADS) framework that significantly extends our previously proposed GAD model, InCTRL.	Jiawen Zhu; Mengjia Niu; Guansong Pang;	arxiv-cs.CV	2026-04-06
101	Hierarchical Point-Patch Fusion with Adaptive Patch Codebook for 3D Shape Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: They often fail to generalize across diverse anomaly types and scales, such as global geometric errors (e.g., planar shifts, angle misalignments), and are sensitive to noisy or incomplete local points during training. To address these limitations, we propose a hierarchical point-patch anomaly scoring network that jointly models regional part features and local point features for robust anomaly reasoning.	XUEYANG KANG et. al.	arxiv-cs.CV	2026-04-05
102	Anomaly Detection in IoT Networks Using Machine Learning Algorithms Related Papers Related Patents Related Grants Related Venues Related Experts View Save		International Research Journal of Modernization in …	2026-04-04
103	Unsupervised Anomaly Detection in Brain FDG PET with Deep Generative Models: An Experimental Analysis of Model Variability and Mitigation Strategies Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Unsupervised anomaly detection allows identifying anomalies from unlabeled data, making it useful for neuroimaging analysis and computer-aided diagnosis. Given an individual’s …	Maelys Solal; André Pascaline; Ninon Burgos;	Medical Imaging 2026: Image Processing	2026-04-03
104	Matrix Profile for Time-Series Anomaly Detection: A Reproducible Open-Source Benchmark on TSB-AD Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Matrix Profile (MP) methods are an interpretable and scalable family of distance-based methods for time-series anomaly detection, but strong benchmark performance still depends on design choices beyond a vanilla nearest-neighbor profile. This technical report documents an open-source Matrix Profile for Anomaly Detection (MMPAD) submission to TSB-AD, a benchmark that covers both univariate and multivariate time series.	Chin-Chia Michael Yeh;	arxiv-cs.LG	2026-04-02
105	Modulate-and-Map: Crossmodal Feature Mapping with Cross-View Modulation for 3D Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present ModMap, a natively multiview and multimodal framework for 3D anomaly detection and segmentation.	Alex Costanzino; Pierluigi Zama Ramirez; Giuseppe Lisanti; Luigi Di Stefano;	arxiv-cs.CV	2026-04-02
106	Open-Set Supervised 3D Anomaly Detection: An Industrial Dataset and A Generalisable Framework for Unknown Defects Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We first adapt general open-set anomaly detection methods to accommodate 3D point cloud inputs better. Building upon this, we propose Open3D-AD, a point-cloud-oriented approach that leverages normal samples, simulated anomalies, and partially observed real anomalies to model the probability density distributions of normal and anomalous data.	HANZHE LIANG et. al.	arxiv-cs.CV	2026-04-01
107	A New Method for Generating Simulated Anomaly Images Based on Perlin Noise Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection methods require learning only normal images to identify various types of anomalous images, thereby enabling broad applications. Some anomaly detection methods …	CHENXIN LI et. al.	Journal of Physics: Conference Series	2026-04-01
108	Statistical Contrastive Learning for Spatio-Temporal Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Zhiwei Zhen; Yuzhou Chen; Yulia R. Gel;	Data Science in Science	2026-03-31
109	Deep Learning-Based Anomaly Detection in Spacecraft Telemetry on Edge Devices Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Spacecraft anomaly detection is critical for mission safety, yet deploying sophisticated models on-board presents significant challenges due to hardware constraints. This paper investigates three approaches for spacecraft telemetry anomaly detection — forecasting & threshold, direct classification, and image classification — and optimizes them for edge deployment using multi-objective neural architecture optimization on the European Space Agency Anomaly Dataset.	Christopher Goetze; Tim Schlippe; Daniel Lakey;	arxiv-cs.LG	2026-03-31
110	A Consensus-Based Multi-Model Framework for Anomaly Detection in High-Dimensional Astronomical Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Many traditional approaches to anomaly detection, including rules-based approaches and single-model machine learning methods, do not work reliably for detecting anomalies because they are sensitive to errors in the data caused by noise and often rely on the assumption that the data has a particular distribution of values. To address this problem, this paper presents a new framework for multi-model anomaly detection using an agreement-based approach that incorporates six anomaly detection algorithms: Isolation Forest, One-Class Support Vector Machine, Local Outlier Factor, DBSCAN, Elliptic Envelope, and Random Forest.	Sneha Rawat;	International Journal for Research in Applied Science and …	2026-03-31
111	Stability and Error Structure Analysis of Generative Adversarial Network–Based Architectures in Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents a controlled comparative evaluation of three GAN-based architectures, GANAD, N-GAN, and Net-GAN, under uni%ed experimental conditions.	Begüm Çorbacıoğlu; Şafak Durukan Odabaşı;	ELECTRICA	2026-03-30
112	Comparative Study on Anomaly Detection Models to Infer Workers’ Walking Hazards Using Video Keypoint Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Taeyoon Kim; Sungjoo Hwang; Siyeon Kim;	Journal of Construction Automation and Robotics	2026-03-30
113	Unsupervised Anomaly Detection on Attributed Multiplex Heterogeneous Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yuehang Cao; Kai Wang; Xuan Wei; Xiang Zhao;	Data Science and Engineering	2026-03-28
114	Fully Autonomous Z-Score-Based TinyML Anomaly Detection on Resource-Constrained MCUs Using Power Side-Channel Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a fully autonomous Tiny Machine Learning (TinyML) Z-Score-based anomaly detection system deployed on a low-power microcontroller for real-time monitoring of appliance behavior using power side-channel data.	Abdulrahman Albaiz; Fathi Amsaad;	arxiv-cs.LG	2026-03-28
115	Adversarial-Robust Multivariate Time-Series Anomaly Detection Via Joint Information Retention Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose ARTA (Adversarially Robust multivariate Time-series Anomaly detection via joint information retention), a joint training framework that improves detector robustness through a principled min-max optimization objective.	Hadi Hojjati; Narges Armanfard;	arxiv-cs.LG	2026-03-26
116	Signal-Aware Contrastive Latent Spaces for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a signal-aware latent space construction using supervised contrastive learning trained on simulated Standard Model backgrounds and a diverse set of hypothesized Beyond the Standard Model (BSM) signals.	Runze Li; Benjamin Nachman; Dennis Noll;	arxiv-hep-ph	2026-03-26
117	Towards Video Anomaly Detection from Event Streams: A Baseline and Benchmark Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we take the first major step toward establishing event-based VAD as a unified research direction.	PENG WU et. al.	arxiv-cs.CV	2026-03-25
118	URA-Net: Uncertainty-Integrated Anomaly Perception and Restoration Attention Network for Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, these methods may suffer from over-generalization, enabling them to reconstruct anomalies well, which leads to poor detection performance. To address this issue, instead of focusing solely on normality reconstruction, we propose an innovative Uncertainty-Integrated Anomaly Perception and Restoration Attention Network (URA-Net), which explicitly restores abnormal patterns to their corresponding normality.	WEI LUO et. al.	arxiv-cs.CV	2026-03-24
119	AI-Driven Anomaly Detection in Big Data Streams: A Case Study on IoT Healthcare ECG Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents an AI-driven approach for anomaly detection in ECG time-series data using unsupervised learning techniques, namely Isolation Forest and Local Outlier Factor (LOF).	Sreerasmi V M;	International Journal for Research in Applied Science and …	2026-03-23
120	Exploring Multimodal Prompts For Unsupervised Continuous Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing UCAD approaches that rely solely on visual information are insufficient to capture the manifold of normality in complex scenes, thereby impeding further gains in anomaly detection accuracy. To overcome this limitation, we propose an unsupervised continual anomaly detection framework grounded in multimodal prompting.	Mingle Zhou; Jiahui Liu; Jin Wan; Gang Li; Min Li;	arxiv-cs.CV	2026-03-23
121	Pseudo Anomalies and Hard Sample Mining for Ventricular Arrhythmia Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose a novel anomaly detection framework named PHVA (Pseudo-data and Hard-sample mining for VA detection) based on one-class anomaly detection, where only normal ECGs are used for training, while pseudo-anomalies are generated through self-supervised modules.	HAOYI FAN et. al.	IEEE journal of biomedical and health informatics	2026-03-23
122	Multimodal Industrial Anomaly Detection Via Geometric Prior Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose a novel Geometric Prior-based Anomaly Detection network (GPAD).	MIN LI et. al.	arxiv-cs.CV	2026-03-23
123	Modeling Quantum Federated Autoencoder for Anomaly Detection in IoT Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a Quantum Federated Autoencoder for Anomaly Detection, a framework that leverages quantum federated learning for efficient, secure, and distributed processing in IoT networks.	Devashish Chaudhary; Sutharshan Rajasegarar; Shiva Raj Pokhrel;	arxiv-quant-ph	2026-03-23
124	Hyperspectral Anomaly Detection Research Fusing Global and Nonlocal Low-rank Factorization and Nonconvex Sparse Constraints Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces the existing advanced low-rank denoising technique, Global and Nonlocal Low-Rank Factorization (GLF), for anomaly detection as a background modeling tool to obtain residual images.	Yujie Gao; Jiayi Hu; Xiaomeng Hu;	Advances in Engineering Innovation	2026-03-20
125	Generative AI-based Approach for Player Behavior Analysis and Gray Area Identification Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Detecting exploitative or unethical player behavior in online gaming platforms is challenging due to ambiguous gray-area actions that are neither clearly legitimate nor illegal. …	Vinay K; Sriram Sankaran;	Frontiers in artificial intelligence	2026-03-20
126	AnomalyTCN: Efficient Contrastive-based Time Series Anomaly Detection with Pure Convolution Structure Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Donghao Luo; Xue Wang;	Neural networks : the official journal of the International …	2026-03-20
127	Dual-Encoder Generative Anomaly Detection for Casting Surface Defect Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Seongmin Kwak; Sooyoung Lee;	International Journal of Precision Engineering and …	2026-03-20
128	Generative AI-based Approach for Player Behavior Analysis and Gray Area Identification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods This study presents an interpretable behavior analysis framework combining anomaly detection, synthetic data augmentation using Conditional Tabular GAN (CTGAN), and ensemble learning with post-hoc explainability.	Vinay K.; Sriram Sankaran;	Frontiers in Artificial Intelligence	2026-03-20
129	Demographic-Aware Self-Supervised Anomaly Detection Pretraining for Equitable Rare Cardiac Diagnosis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we developed an AI-assisted two-stage ECG framework integrating self-supervised anomaly detection with demographic-aware representation learning.	CHAOQIN HUANG et. al.	arxiv-cs.CV	2026-03-20
130	FB-CLIP: Fine-Grained Zero-Shot Anomaly Detection with Foreground-Background Disentanglement Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose FB-CLIP, a framework that enhances anomaly localization via multi-strategy textual representations and foreground-background separation.	MING HU et. al.	arxiv-cs.CV	2026-03-19
131	An Efficient Real-Time Anomaly Detection Scheme for Water Quality Monitoring Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present an efficient real-time anomaly detection scheme which boosts detection accuracy while mitigating human effort.	Wenjie Guo; Leijun Huang; Yang Li; Wenxian Luo;	Water	2026-03-19
132	ICLAD: In-Context Learning for Unified Tabular Anomaly Detection Across Supervision Regimes Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose ICLAD, an in-context learning foundation model for tabular anomaly detection that generalizes across both datasets and supervision regimes.	Jack Yi Wei; Narges Armanfard;	arxiv-cs.LG	2026-03-19
133	Unsupervised Symbolic Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose SYRAN, an unsupervised anomaly detection method based on symbolic regression.	Md Maruf Hossain; Tim Katzke; Simon Klüttermann; Emmanuel Müller;	arxiv-cs.LG	2026-03-18
134	BoundAD: Boundary-Aware Negative Generation for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Most existing methods rely on prior anomaly injection, while overlooking the potential of generating hard negatives near the data manifold boundary directly from normal samples themselves. To address this issue, we propose a reconstruction-driven boundary negative generation framework that automatically constructs hard negatives through the reconstruction process of normal samples.	Xiancheng Wang; Lin Wang; Zhibo Zhang; Rui Wang; Minghang Zhao;	arxiv-cs.LG	2026-03-18
135	RangeAD: Fast On-Model Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce On-Model AD, a setting for anomaly detection that explicitly leverages access to a related machine learning model.	Luca Hinkamp; Simon Klüttermann; Emmanuel Müller;	arxiv-cs.LG	2026-03-18
136	Multivariate Time Series Anomaly Detection for Industrial System Reliability Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, most existing approaches cannot simultaneously mitigate these intertwined challenges. To address this gap, this paper proposes a deep Transformer-based anomaly detection model tailored for industrial system reliability.	lin wang; Zhipeng Chai; Wei Wang; Ziyang Liu; Ting Liu;	Engineering Research Express	2026-03-18
137	AI Driven VANET Assisted Prediction and Anomaly Detection in Active Suspension Systems: Modeling and Performance Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper suggests an AI‐driven, VANET‐assisted architecture for real‐time active suspension system prediction and anomaly detection.	Fengkai Guo; Caiyun Duan;	Transactions on Emerging Telecommunications Technologies	2026-03-17
138	Research on Magnetic Anomaly Signal Detection Based on CNN-LSTM Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Moreover, effective preprocessing of the dataset is crucial. To address these issues, this paper proposes a neural network method based on Orthogonal Basis Function (OBF) feature detection.	honglei Wang; chunxu jiang; Yingda Ren; Lichao Ding;	Measurement Science and Technology	2026-03-17
139	A Lightweight and Robust Method for Electrocardiogram Anomaly Detection and Localization Using Multi-scale Masked Autoencoder Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing anomaly detection methods often rely on R-peak detection or heartbeat segmentation, which increases preprocessing complexity and reduces robustness to signal variability. To address these limitations, we propose MMAE-ECG, a multi-scale masked autoencoder designed to capture both global and local dependencies without such preprocessing steps.	YA ZHOU et. al.	PloS one	2026-03-17
140	Detection of Rare Medical Events in Electronic Health Records Using Machine Learning: Current Practices and Suggestions – A Scoping Review Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Detecting small subgroups in EHR data, so-called anomaly detection, is an emerging approach, yet organized documentation on current practices remains scarce. This scoping review examines medical anomaly detection based on routine healthcare data stored in EHRs and formulated alternative approaches in case suboptimal practices were noticed.	Biniyam Gebeyehu; Bennett Kleinberg; Katrijn Van Deun; Esther de Vries;	PLOS One	2026-03-16
141	Detection of Rare Medical Events in Electronic Health Records Using Machine Learning: Current Practices and Suggestions – A Scoping Review Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Detecting small subgroups in EHR data, so-called anomaly detection, is an emerging approach, yet organized documentation on current practices remains scarce. This scoping review examines medical anomaly detection based on routine healthcare data stored in EHRs and formulated alternative approaches in case suboptimal practices were noticed.	Biniyam Gebeyehu; Bennett Kleinberg; Katrijn Van Deun; Esther de Vries;	PloS one	2026-03-16
142	Improving Anomaly Detection with Foundation-model Synthesis and Wavelet-domain Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Save	WENSHENG WU et. al.	Neural networks : the official journal of the International …	2026-03-14
143	TACTIC for Navigating The Unknown: Tabular Anomaly DeteCTion Via In-Context Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we study in-context models for anomaly detection and show that the unsupervised extensions to TabPFN exhibit unstable behavior, particularly in noisy or contaminated contexts, in addition to the high computational cost.	Patryk Marszałek; Tomasz Kuśmierczyk; Marek Śmieja;	arxiv-cs.LG	2026-03-14
144	Towards Automated Self-Supervised Learning for Truly Unsupervised Graph Anomaly Detection (Abstract Reprint) Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Self-supervised learning (SSL) is an emerging paradigm that exploits supervisory signals generated from the data itself, and many recent studies have leveraged SSL to conduct …	Zhong Li; Yuhang Wang; M. Leeuwen;	AAAI Conference on Artificial Intelligence	2026-03-14
145	Hybrid Anomaly Detection Using Vision Transformers and Convolutional Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes a hybrid anomaly detection model that integrates Vision Transformers(ViTs) and Convolutional Neural Networks(CNNs) for graph-based classification of network behaviors.	Ming-Yang Su; Yu-Wen Chou; Yun-Rou Zhou; Pei-Ying Yu;	International Journal of Software Engineering and Knowledge …	2026-03-13
146	Unsupervised Multimodal Anomaly Detection Via Stable Reconstruction Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Seyoung Jeong; Sang-Jun Lee;	Journal of Institute of Control, Robotics and Systems	2026-03-12
147	Dual-stream Background Modeling Network with Anomaly Suppression for Hyperspectral Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yu Huo; Sha Wang; Chenhao Wang; Min Zhang; Hai Wang;	International Journal of Applied Earth Observation and …	2026-03-11
148	An Improved IForest-based Method for Electricity Consumption Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The widespread application of artificial intelligence and intelligent algorithms in large-scale time-series data analysis has provided new technical approaches for detecting …	SHUHAN HUA et. al.	International Conference on New Power System and Power …	2026-03-10
149	AI-Based Anomaly Detection in Air-Gapped Environments Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Abhishek Kumar; Meenakshi Saini;	International Journal of Science and Research (IJSR)	2026-03-10
150	Temporal-Conditioned Normalizing Flows for Multivariate Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces temporal-conditioned normalizing flows (tcNF), a novel framework that addresses anomaly detection in time series data with accurate modeling of temporal dependencies and uncertainty.	David Baumgartner; Helge Langseth; Kenth Engø-Monsen; Heri Ramampiaro;	arxiv-cs.LG	2026-03-10
151	TA-GGAD: Testing-time Adaptive Graph Model for Generalist Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Based on the modeling of the issue $\mathcal{AD}$, we introduce a novel graph foundation model for anomaly detection.	XIONG ZHANG et. al.	arxiv-cs.LG	2026-03-10
152	GPT-based Self-supervised Anomaly Detection in Command Lines Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Miles Q. Li; Julien Keutchayan; François Charest; Benjamin C. M. Fung;	Journal of Computer Virology and Hacking Techniques	2026-03-09
153	Graph Anomaly Detection Method Based on Fused Representation of Nodes and Edges Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Graph anomaly detection is a fundamental task in graph data mining, with significant applications in areas such as financial fraud detection and social network analysis. …	S. Li; Na Liu; Changbo Wang;	International Conference on Machine Learning and Artificial …	2026-03-09
154	An Interpretable Generative Framework for Anomaly Detection in High-Dimensional Financial Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose ReGEN-TAD, an interpretable generative framework that integrates modern machine learning with econometric diagnostics for anomaly detection.	Waldyn G Martinez;	arxiv-stat.ML	2026-03-08
155	Transformer-vae for Contextual Anomaly Detection in Text Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Lazhar Farek; Amira Benaidja;	International Journal of Machine Learning and Cybernetics	2026-03-07
156	DQE: A Semantic-Aware Evaluation Metric for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we revisit the evaluation of time series anomaly detection from the perspective of detection semantics and propose a novel metric for more comprehensive assessment.	YUEWEI LI et. al.	arxiv-cs.LG	2026-03-06
157	Anomaly Detection and Fault Diagnosis of Main Steam Temperature of The Thermal Power Unit Based on TGAN-SATCN Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: A deep learning anomaly detection and fault diagnosis method based on a temporal generative adversarial network (TGAN) and temporal convolutional network (TCN) is proposed to …	Guoxin Su; Wenliang Zhang; Hongfu Zhang; Long Liu; Ming Su;	Frontiers in Energy Research	2026-03-05
158	Federated Learning–based Anomaly Detection for Privacy-preserving in IoT-enabled Industrial Control Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a federated learning–based anomaly detection framework that enables collaborative model training across distributed edge devices while preserving data locality.	Obi Ofuka Princewill; Essien Eyo; Bassey I. Ele;	Journal of Statistical Sciences and Computational …	2026-03-05
159	Fog Enabled Anomaly Detection System for Sensors’ Anomaly in IoT Environment Using Machine Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Mohd Asifuddola; Mohd Ahsan Siddiqui; Mala Kalra; C Rama Krishna; Ab Rouf Khan;	International Journal of System Assurance Engineering and …	2026-03-04
160	What Knowledge Transfers in Tabular Anomaly Detection? A Teacher–Student Distillation Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose KD-AnomalyNet, a teacher–student framework that distills anomaly knowledge from a high-capacity ensemble into a lightweight neural model for efficient inference.	Tea Krčmar; Dina Šabanović; Miljenko Švarcmajer; Ivica Lukić;	Machine Learning and Knowledge Extraction	2026-03-03
161	Dual Distillation for Few-Shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce D$^2$4FAD, a novel dual distillation framework for few-shot anomaly detection that identifies anomalies in previously unseen tasks using only a small number of normal reference images.	LE DONG et. al.	arxiv-cs.CV	2026-03-02
162	UMIAD-EGMF: Unsupervised Medical Image Anomaly Detection Based on Edge Guidance and Multi-scale Flow Fusion Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Existing unsupervised anomaly detection methods, which are the mainstream approaches, often struggle with issues such as blurred edges and varying scales of abnormal regions. To address these issues, a novel unsupervised method for medical image anomaly detection is proposed: unsupervised medical image anomaly detection based on edge guidance and multi-scale flow fusion (UMIAD-EGMF).	Zhirong Li; Guangfeng Lin; Dou Zhang; Rongxin Huang; Jing Yang;	Visual computing for industry, biomedicine, and art	2026-03-02
163	Quantum Enhanced Ensemble GANs for Anomaly Detection in Continuous Biomanufacturing Related Papers Related Patents Related Grants Related Venues Related Experts View Save	RAJIV KAILASANATHAN et. al.	Industrial & Engineering Chemistry Research	2026-03-02
164	Weakly Supervised Video Anomaly Detection with Anomaly-Connected Components and Intention Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, a key limitation persists in WS-VAD, as dense frame-level annotations are absent, which often leaves existing methods struggling to learn anomaly semantics effectively. To address this issue, we propose a novel framework named LAS-VAD, short for Learning Anomaly Semantics for WS-VAD, which integrates anomaly-connected component mechanism and intention awareness mechanism.	Yu Wang; Shengjie Zhao;	arxiv-cs.CV	2026-02-28
165	An Efficient Unsupervised Federated Learning Approach for Anomaly Detection in Heterogeneous IoT Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study we propose an efficient unsupervised FL framework that enhances anomaly detection by leveraging shared features from two distinct IoT datasets: one focused on anomaly detection and the other on device identification, while preserving dataset-specific features.	Mohsen Tajgardan; Atena Shiranzaei; Mahdi Rabbani; Reza Khoshkangini; Mahtab Jamali;	arxiv-cs.LG	2026-02-27
166	DF-TransVAE: A Deep Fusion Network for Binary Classification-Based Anomaly Detection in Internet User Behavior Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Our results indicate that the deep integration mechanism we propose effectively addresses the limitations of conventional Transformer–VAE combinations.	HUIHUI FAN et. al.	Applied Sciences	2026-02-26
167	A Review of Flight Abnormal Behavior Analysis and Trajectory Anomaly Detection Methods Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a comprehensive review that covers flight abnormal behavior analysis and trajectory anomaly detection.	Yexin Wu; Yifei Zhao; Hongyong Wang;	Aerospace	2026-02-26
168	Anomaly Detection with Spiking Neural Networks for LHC Physics Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper investigates AutoEncoders built using neuromorphic Spiking Neural Networks (SNNs) for this purpose.	Barry Dillon; Aqib Javed; J Harkin;	Machine Learning: Science and Technology	2026-02-25
169	Fungal Biohybrid Substrates for Resilient Sensing and Embodied Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Andrew Adamatzky;	BioSystems	2026-02-24
170	Designing Efficient Anomaly Detection Systems Using Deep Learning Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper aims to explore the role of deep learning (DL) in developing effective anomaly detection systems (ADSs).	Arash Heidari; Nima Jafari; Sherali Zeadally;	International Journal of Pervasive Computing and …	2026-02-24
171	Semantic Augmentation Variational Autoencoder for Unsupervised Anomaly Detection in Retinal OCT Images Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Existing methods address these challenges by flattening retinal layers, normalizing thickness, or leveraging reflectance priors, but their reliance on complex pre- and post-processing introduces uncertainties and limits end-to-end clinical applicability. To overcome these issues, we propose a novel semantic augmentation variational autoencoder (SeAugVAE) for unsupervised anomaly detection in retinal OCT images.	XUEYING ZHOU et. al.	IEEE transactions on medical imaging	2026-02-23
172	Unsupervised Anomaly Detection in NSL-KDD Using $β$-VAE: A Latent Space and Reconstruction Error Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper explores an unsupervised approach to anomaly detection in network traffic using $β$-Variational Autoencoders on the NSL-KDD dataset.	Dylan Baptiste; Ramla Saddem; Alexandre Philippot; François Foyer;	arxiv-cs.LG	2026-02-23
173	Advanced Anomaly Detection in Server Environments Against Emerging Cyber-Attack Patterns Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This research proposes an advanced anomaly detection framework capable of identifying unusual patterns and behaviors in server operations, specifically addressing emerging forms of cyber-attacks.	V T Ram Pavan Kumar;	International Journal for Research in Applied Science and …	2026-02-21
174	EAGLE: Expert-Augmented Attention Guidance for Tuning-Free Industrial Anomaly Detection in Multimodal Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose expert-augmented attention guidance for industrial anomaly detection in MLLMs (EAGLE), a tuning-free framework that integrates outputs from expert model to guide MLLMs toward both accurate detection and interpretable anomaly descriptions.	Xiaomeng Peng; Xilang Huang; Seon Han Choi;	arxiv-cs.CV	2026-02-19
175	BPGV: Behavioral Provenance Graph Views to Enhance Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Michael Zipperle; Yu Zhang; Min Wang; Elizabeth Chang; Tharam Dillon;	International Journal of Information Management Data …	2026-02-18
176	Cross Pseudo Labeling For Weakly Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose CPL-VAD, a dual-branch framework with cross pseudo labeling.	Lee Dayeon; Kim Dongheyong; Park Chaewon; Woo Sungmin; Lee Sangyoun;	arxiv-cs.CV	2026-02-18
177	RELIABILITY-AWARE ANOMALY DETECTION FOR STREAMING MULTIMODAL TIME SERIES IN DECISION SUPPORT SYSTEMS Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper formulates the problem of FAR-budgeted anomaly detection and proposes a Reliability-Constrained Anomaly Detection (RC-AD) method.	Illia Uzun;	International Scientific Unity	2026-02-18
178	StructCore: Structure-Aware Image-Level Scoring for Training-Free Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose StructCore, a training-free, structure-aware image-level scoring method that goes beyond max pooling.	JOONGWON CHAE et. al.	arxiv-cs.CV	2026-02-18
179	Topological Anomaly Quantification for Semi-supervised Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, these methods lack a quantitative assessment of anomalies, hindering the reliability of the generated ones. To overcome this limitation, we propose a generative graph anomaly detection model based on topological anomaly quantification (TAQ-GAD).	TING GUO et. al.	iclr	2026-02-17
180	PaAno: Patch-Based Representation Learning for Time-Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we propose Patch-based representation learning for time-series Anomaly detection (PaAno), a lightweight yet effective method for fast and efficient time-series anomaly detection.	Jinju Park; Seokho Kang;	iclr	2026-02-17
181	MRAD: Zero-Shot Anomaly Detection with Memory-Driven Retrieval Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Zero-shot anomaly detection (ZSAD) often leverages pretrained vision or vision-language models, but many existing methods use prompt learning or complex modeling to fit the data distribution, resulting in high training or inference cost and limited cross-domain stability. To address these limitations, we propose Memory-Retrieval Anomaly Detection method (MRAD), a unified framework that replaces parametric fitting with a direct memory retrieval.	Chaoran Xu; Chengkan Lv; Qiyu Chen; Feng Zhang; Zhengtao Zhang;	iclr	2026-02-17
182	Free Point-wise Anomaly Detection Via Fold-bifurcation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce FOLD (Point-wise Anomaly Detection via fold-bifurcation), a framework that reframes detection as tracking a system’s proximity to a critical transition.	Sheo yon Jhin; Noseong Park;	iclr	2026-02-17
183	When Foundation Models Are One-Liners: Limitations and Future Directions for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we focus on time-series anomaly detection, in which time-series foundation models detect anomalies based on the reconstruction or forecasting error.	Xiaokun Zhu; Louis Carpentier; Mathias Verbeke;	iclr	2026-02-17
184	Foundation Visual Encoders Are Secretly Few-Shot Anomaly Detectors Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Large-scale pre-training of foundation visual encoders has advanced many fields, as the enormous quantity of data helps to learn the general distribution of normal images. We observe that the anomaly amount in an image directly correlates with the difference in the learnt embeddings and utilize this to design a few-shot anomaly detector termed FoundAD.	GUANGYAO ZHAI et. al.	iclr	2026-02-17
185	Towards Anomaly-Aware Pre-Training and Fine-Tuning for Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Graph anomaly detection (GAD) has garnered increasing attention in recent years, yet remains challenging due to two key factors: (1) label scarcity stemming from the high cost of annotations and (2) homophily disparity at node and class levels. In this paper, we introduce Anomaly-Aware Pre-Training and Fine-Tuning (APF), a targeted and effective framework to mitigate the above challenges in GAD.	YUNHUI LIU et. al.	iclr	2026-02-17
186	Complexity- and Statistics-Guided Anomaly Detection in Time Series Foundation Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We identify two key challenges when applying TFMs to reconstruction-based anomaly detection and propose solutions.	JONGWON KIM et. al.	iclr	2026-02-17
187	Contextual and Seasonal LSTMs for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing reconstruction-based and prediction-based methods struggle to capture certain subtle anomalies, particularly small point anomalies and slowly rising anomalies. To address these challenges, we propose a novel prediction-based framework named Contextual and Seasonal LSTMs (CS-LSTMs).	LINGPEI ZHANG et. al.	iclr	2026-02-17
188	AnomaMind: Agentic Time Series Anomaly Detection with Tool-Augmented Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We argue that these limitations stem from the lack of adaptive feature preparation, reasoning-aware detection, and iterative refinement during inference. To address these challenges, we propose AnomaMind, an agentic time series anomaly detection framework that reformulates anomaly detection as a sequential decision-making process.	Xiaoyu Tao; Yuchong Wu; Mingyue Cheng; Ze Guo; Tian Gao;	arxiv-cs.LG	2026-02-14
189	Universal Transformation of One-Class Classifiers for Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a dataset folding method that transforms an arbitrary one-class classifier-based anomaly detector into a fully unsupervised method.	Declan McIntosh; Alexandra Branzan Albu;	arxiv-cs.CV	2026-02-13
190	A Comprehensive Review on Graph-Based Anomaly Detection: Approaches for Intrusion Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a phased graph-based anomaly detection methodology for intrusion detection.	Nimesha Dilini; Nan Sun; Yuantian Miao; Nour Moustafa;	Applied Sciences	2026-02-13
191	FRLog: Log Anomaly Detection Based on Three-Stage Training with Reft Fine-Tuning for Large Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To this end, this paper proposes FRLog, a log anomaly detection framework based on large language model, which realizes contextualized semantic embeddings of log sequences by fusing BERT and LLaMA models, thereby enabling more accurate log anomaly detection.	KEYUAN QIU et. al.	Journal of Artificial Intelligence and Soft Computing …	2026-02-13
192	Unsupervised Learning Framework for Cyber Threat Detection, Anomaly Identification, and Alert Prioritization Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents a custom AI-driven framework that leverages unsupervised learning techniques to support SOC analysts in cyber threat detection, anomaly identification, and alert prioritization.	Emmanuel Okafor; Seokhee Lee;	Applied Sciences	2026-02-13
193	Power Interpretable Causal ODE Networks: A Unified Model for Explainable Anomaly Detection and Root Cause Analysis in Power Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing machine learning models for time series anomaly detection often operate as black boxes, offering only binary outputs without any explanation, such as identifying anomaly type and origin. To address this challenge, we propose Power Interpretable Causality Ordinary Differential Equation (PICODE) Networks, a unified, causality-informed architecture that jointly performs anomaly detection along with the explanation why it is detected as an anomaly, including root cause localization, anomaly type classification, and anomaly shape characterization.	Yue Sun; Likai Wang; Rick S. Blum; Parv Venkitasubramaniam;	arxiv-cs.LG	2026-02-12
194	DMP-3DAD: Cross-Category 3D Anomaly Detection Via Realistic Depth Map Projection with Few Normal Samples Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose DMP-3DAD, a training-free framework for cross-category 3D anomaly detection based on multi-view realistic depth map projection.	ZI WANG et. al.	arxiv-cs.CV	2026-02-11
195	Interpretable Graph-Level Anomaly Detection Via Contrast with Normal Prototypes Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Although some recent methods have made attempts to provide explanations for anomaly detection results, they either provide explanations without referencing normal graphs, or rely on abstract latent vectors as prototypes rather than concrete graphs from the dataset. To address these limitations, we propose Prototype-based Graph-Level Anomaly Detection (ProtoGLAD), an interpretable unsupervised framework that provides explanation for each detected anomaly by explicitly contrasting with its nearest normal prototype graph.	Qiuran Zhao; Kai Ming Ting; Xinpeng Li;	arxiv-cs.LG	2026-02-11
196	Real-Time Proactive Anomaly Detection Via Forward and Backward Forecast Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we introduce two proactive anomaly detection frameworks: the Forward Forecasting Model (FFM) and the Backward Reconstruction Model (BRM).	Luis Olmos; Rashida Hasan;	arxiv-cs.LG	2026-02-11
197	Enhancing Weakly Supervised Multimodal Video Anomaly Detection Through Text Guidance Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Furthermore, multimodal fusion often suffers from redundancy and imbalance. To address these issues, we propose a novel text-guided framework.	Shengyang Sun; Jiashen Hua; Junyi Feng; Xiaojin Gong;	arxiv-cs.CV	2026-02-11
198	Anomaly Detection Using Machine Learning for Robotics Environments on 5G Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work underscores the importance of developing and refining machine learning (ML) methods to meet the specific demands of anomaly detection in 5G-powered environments.	Mikel Dean Oses; Aitor Domec Paz; Santiago Figueroa-Lorenzo; Saioa Arrizabalaga; Ricardo Rodriguez-Jorge;	Technologies	2026-02-09
199	Benchmarking Anomaly Detection Across Heterogeneous Cloud Telemetry Datasets Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we evaluate four deep learning models, GRU, TCN, Transformer, and TSMixer.	Mohammad Saiful Islam; Andriy Miranskyy;	arxiv-cs.NI	2026-02-07
200	Semantic-Deviation-Anchored Multi-Branch Fusion for Unsupervised Anomaly Detection and Localization in Unstructured Conveyor-Belt Coal Scenes Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: These characteristics weaken the stability and regularity assumptions that many anomaly detection methods rely on in structured industrial settings, leading to notable performance degradation. To support evaluation and comparison in this setting, we construct \textbf{CoalAD}, a benchmark for unsupervised foreign-object anomaly detection with pixel-level localization in coal-stream scenes.	Wenping Jin; Yuyang Tang; Li Zhu;	arxiv-cs.CV	2026-02-07
201	Compact, Eye-safe Polarization Light Detection and Ranging System at 1550 Nm Wavelength for Aerosol Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Sebastian Zajonz; Oliver Kliebisch; Frank Duschek; Arne Walter; Thomas Dekorsy;	Applied Optics	2026-02-06
202	KRONE: Hierarchical and Modular Log Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose KRONE, the first hierarchical anomaly detection framework that automatically derives execution hierarchies from flat logs for modular multi-level anomaly detection.	LEI MA et. al.	arxiv-cs.DB	2026-02-06
203	A Comparative Study of RQA-Guided Attention Mechanisms with LSTM Autoencoder for Bearing Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we propose a Recurrence Quantification Analysis-Aware Attention (RQAA) framework that systematically injects chaos-theoretic descriptors into the attention mechanism of LSTM-based autoencoders for unsupervised anomaly detection.	Ayşenur Hatipoğlu; Ersen Yılmaz;	Sensors (Basel, Switzerland)	2026-02-04
204	Anomaly Detection Algorithm of Meter Reading Messages for Power Line Communication Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Ultimately, an anomaly detection algorithm based on the ICNN is developed.	Zhixiong Chen; Yufan Yan; Ziyi Wu; Jiajing Li;	Applied Sciences	2026-02-04
205	Balanced Anomaly-guided Ego-graph Diffusion Model for Inductive Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: These challenges are interdependent: static transductive frameworks limit effective data augmentation, while imbalance exacerbates model distortion in inductive learning settings. To address these challenges, we propose a novel data-centric framework that integrates dynamic graph modeling with balanced anomaly synthesis.	CHUNYU WEI et. al.	arxiv-cs.LG	2026-02-04
206	Multi-Aspect Mining and Anomaly Detection for Heterogeneous Tensor Streams Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: (ii) They discretize timestamps, failing to track the temporal dynamics of streams(e.g., trends, abnormal events), which makes them ineffective for detecting anomalies at the group level, referred to as ‘group anomalies’ (e.g, DoS attacks). To address these challenges, we propose HeteroComp, a method for continuously summarizing heterogeneous tensor streams into ‘components’ representing latent groups in each attribute and their temporal dynamics, and detecting group anomalies.	Soshi Kakio; Yasuko Matsubara; Ren Fujiwara; Yasushi Sakurai;	arxiv-cs.LG	2026-02-04
207	Anomaly Detection Via Mean Shift Density Enhancement Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose Mean Shift Density Enhancement (MSDE), a fully unsupervised framework that detects anomalies through their geometric response to density-driven manifold evolution.	Pritam Kar; Rahul Bordoloi; Olaf Wolkenhauer; Saptarshi Bej;	arxiv-cs.LG	2026-02-03
208	SAGE-5GC: Security-Aware Guidelines for Evaluating Anomaly Detection in The 5G Core Network Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a set of Security-Aware Guidelines for Evaluating anomaly detectors in 5G Core Network (SAGE-5GC), driven by domain knowledge and consideration of potential adversarial threats.	CRISTIAN MANCA et. al.	arxiv-cs.LG	2026-02-03
209	Dgaad: A Novel Attention-based Model for HPC Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	XU GAO et. al.	The Journal of Supercomputing	2026-02-02
210	RPG-AE: Neuro-Symbolic Graph Autoencoders with Rare Pattern Mining for Provenance-Based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a neuro-symbolic anomaly detection framework that combines a Graph Autoencoder (GAE) with rare pattern mining to identify APT-like activities in system-level provenance data.	Asif Tauhid; Sidahmed Benabderrahmane; Mohamad Altrabulsi; Ahamed Foisal; Talal Rahwan;	arxiv-cs.LG	2026-02-02
211	Feature Structure Co-optimized Augmented Network for Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yingyue Zhang; Huifang Ma; Rui Bing; Meihuizi Jia; Xiaofei Wang;	Information Processing & Management	2026-02-02
212	AnomalyLVM:Vision-language Models for Zero-shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yuqing Zhao; Min Meng; Jigang Wu;	Expert Syst. Appl.	2026-02-01
213	Anomaly Detection of Ship Behavior Based on Deep Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yaqing Shu; Ao Dong; Chengyong Liu; Langxiong Gan; Lan Song;	Reliab. Eng. Syst. Saf.	2026-02-01
214	Urban Traffic Flow Prediction and Anomaly Detection Via Spatiotemporal Graph Neural Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the rapid development of urban infrastructure, accurate traffic flow prediction and real-time anomaly detection have become critical challenges in intelligent transportation …	Zi Chai;	International Conference on Communication, Information and …	2026-01-31
215	Exploring Autoencoders for Anomaly Detection in Intrusion Detection Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents the development and evaluation of an Intrusion Detection System (IDS) based on a Denoising Autoencoder (DAE).	Awab Khalefa; Ahmet Zengin;	Bilişim Teknolojileri Dergisi	2026-01-31
216	Multi-Cue Anomaly Detection and Localization Under Data Contamination Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose a robust anomaly detection framework that integrates limited anomaly supervision into the adaptive deviation learning paradigm.	Anindya Sundar Das; Monowar Bhuyan;	arxiv-cs.CV	2026-01-30
217	Analyzing Shapley Additive Explanations to Understand Anomaly Detection Algorithm Behaviors and Their Complementarity Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: As a result, the potential of ensemble learning is often limited by the difficulty of identifying models that truly capture different types of irregularities. To address this, we propose a methodology for characterizing anomaly detectors through their decision mechanisms.	Jordan Levy; Paul Saves; Moncef Garouani; Nicolas Verstaevel; Benoit Gaudou;	arxiv-cs.LG	2026-01-30
218	Fast, Robust, and Accurate Anomaly Detection for Multivariate Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Simone Tonini; Andrea Vandin; Francesca Chiaromonte; Daniele Licari; Fernando Barsacchi;	Advances in Data Analysis and Classification	2026-01-30
219	SecuFL-IoT: An Adaptive Privacy-preserving Federated Learning Framework for Anomaly Detection in Smart Industrial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The increasing adoption of Industrial Internet of Things (IIoT) devices introduces significant cybersecurity and privacy challenges, particularly anomaly detection and secure data …	Ali Alqazzaz;	Scientific reports	2026-01-29
220	Anomaly Detection in Brain MRI: A Comprehensive Review Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Jihun Kim; Youmin Shin;	Biomedical Engineering Letters	2026-01-29
221	Modeling Heterogeneous Normality in Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Xiaohui Zhou; Yijie Wang; Hongzuo Xu; Yizhou Li;	Information Processing & Management	2026-01-28
222	Robust ICS Anomaly Detection Using Multi-Scale Temporal Dependencies and Frequency-Domain Features Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Additionally, ICS data often contain high-frequency noise and complex periodic patterns, which traditional methods and standalone models, such as Long Short-Term Memory (LSTM), fail to capture effectively. To address these challenges, we propose a novel anomaly detection framework that leverages Gated Recurrent Units for short-term dynamics and PatchTST for long-term dependencies.	Fang Wang; Haihan Chen; Suyang Wang; Zhongyuan Qin; Fang Dong;	Electronics	2026-01-28
223	LLM-Assisted Logic Rule Learning: Scaling Human Expertise for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a framework that leverages large language models (LLMs) to systematically encode human expertise into interpretable, logic-based rules for detecting anomaly patterns in supply chain time series data.	Haoting Zhang; Shekhar Jain;	arxiv-cs.LG	2026-01-27
224	Anomaly Detection, Filtering and Visualization for Outdoor Photovoltaic Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Goodfriend M. Whyte; Andreas Gerber; Uwe Rau; Bart E. Pieters;	Solar Energy	2026-01-27
225	Anomaly Detection & Classification Using Machine Learning for Campus Surveillance Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Shakshi Richhariya;
226	Multi-faceted Consistency Data Augmentation for Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Tairan Huang; Yili Wang; Qiutong Li; Jianliang Gao;	Inf. Process. Manag.
227	Unsupervised Anomaly Detection Based on Deep Autoencoders, Information Fusion, and Active Sensing Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Structural health monitoring plays a crucial role in ensuring the safety and resilience of engineering structures. Detecting structural anomalies is essential for maintaining the …	ZIXIN WANG et. al.	Structural Health Monitoring	2026-01-23
228	Few-shot Anomaly Detection Via Adaptive Graph Feature Registration Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Gaihua Wang; Sijia Xu; Kehong Li; Keke Ren;	Knowledge and Information Systems	2026-01-22
229	HeadHunt-VAD: Hunting Robust Anomaly-Sensitive Heads in MLLM for Tuning-Free Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, these methods typically rely on textual outputs, which introduces information loss, exhibits normalcy bias, and suffers from prompt sensitivity, making them insufficient for capturing subtle anomalous cues. To address these constraints, we propose HeadHunt-VAD, a novel tuning-free VAD paradigm that bypasses textual generation by directly hunting robust anomaly-sensitive internal attention heads within the frozen MLLM.	Zhaolin Cai; Fan Li; Ziwei Zheng; Haixia Bi; Lijun He;	aaai	2026-01-20
230	CASL: Curvature-Augmented Self-supervised Learning for 3D Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose a Curvature-Augmented Self-supervised Learning (CASL) framework based on a reconstruction paradigm.	YAOHUA ZHA et. al.	aaai	2026-01-20
231	Towards Token-Level Text Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We formally define text anomalies at both document and token-levels, and propose a unified detection framework that operates across multiple levels.	Yang Cao; Bicheng Yu; Sikun Yang; Ming Liu; Yujiu Yang;	arxiv-cs.CL	2026-01-20
232	IAD-R1: Reinforcing Consistent Reasoning in Industrial Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Although Vision-Language Models (VLMs) demonstrate significant advantages in generalization capabilities, their performance in industrial anomaly detection remains limited. To address this challenge, we propose IAD-R1, a universal post-training framework applicable to VLMs of different architectures and parameter scales, which substantially enhances their anomaly detection capabilities.	YANHUI LI et. al.	aaai	2026-01-20
233	Anomaly Detection Based on Hybrid Kernelized Fuzzy Density Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Fuzzy information granulation is a key concept in granular computing, which offers a potent framework for managing uncertainty in mixed-type data and provides a viable pathway for unsupervised anomaly detection.	Kaitian Luo; Shenhong Lei; Chaoqing Li; Yi Li;	Symmetry	2026-01-20
234	CADiff: Context-Aware Diffusion for Controllable Anomaly Generation in Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose CADiff, a context-aware generation framework that reframes anomalies as compositional perturbations.	XUAN TONG et. al.	aaai	2026-01-20
235	Normality-enhanced Knowledge Distillation Network for Unsupervised Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	GANG LI et. al.	Engineering Applications of Artificial Intelligence	2026-01-20
236	Beyond Local Patterns: Multiscale Inconsistency Learning for Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we highlight two key insights: graph neural networks are often suboptimal as feature extractors due to neighborhood aggregation diluting anomaly signals, and reliance on local inconsistency mining is inadequate for comprehensive anomaly detection, as it often fails to identify anomalies hidden within camouflaged communities.	JIE LIAN et. al.	aaai	2026-01-20
237	Survey on AI-Based Reliability and Anomaly Detection in Microservices Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Muzeeb Mohammad;	International Journal of Computer Applications	2026-01-20
238	FDP: A Frequency-Decomposition Preprocessing Pipeline for Unsupervised Anomaly Detection in Brain MRI Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To advance UAD in brain MRI, we conduct the first systematic frequency-domain analysis of pathological signatures, revealing two key properties: (1) anomalies exhibit unique frequency patterns distinguishable from normal anatomy, and (2) low-frequency signals maintain consistent representations across healthy scans.	HAO LI et. al.	aaai	2026-01-20
239	Anomagic: Crossmodal Prompt-driven Zero-shot Anomaly Generation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose Anomagic, a zero-shot anomaly generation method that produces semantically coherent anomalies without requiring any exemplar anomalies.	YUXIN JIANG et. al.	aaai	2026-01-20
240	A Graph Prompt Fine-Tuning Method for WSN Spatio-Temporal Correlation Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, a graph neural network anomaly detection backbone network incorporating spatio-temporal correlation features and a multi-task self-supervised training strategy of pre-training – graph prompting – fine-tuning are designed for the characteristics of WSN graph structure data.	MIAO YE et. al.	arxiv-cs.LG	2026-01-19
241	Toward Faithful Explanations in Acoustic Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we study the interpretability of autoencoder-based models for audio anomaly detection, by comparing a standard autoencoder (AE) with a mask autoencoder (MAE) in terms of detection performance and interpretability.	MAAB ELRASHID et. al.	arxiv-cs.SD	2026-01-18
242	Wavelet-Aware Anomaly Detection in Multi-Channel User Logs Via Deviation Modulation and Resolution-Adaptive Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: These logs are often multi-channel, non-stationary, and anomalies are rare, making anomaly detection challenging. To address these issues, we propose a novel framework that integrates wavelet-aware modulation, multi-resolution wavelet decomposition, and resolution-adaptive attention for robust anomaly detection.	Kaichuan Kong; Dongjie Liu; Xiaobo Jin; Shijie Xu; Guanggang Geng;	arxiv-cs.LG	2026-01-17
243	QUPID: A Partitioned Quantum Neural Network for Anomaly Detection in Smart Grid Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose QUPID, a partitioned quantum neural network (PQNN) that outperforms traditional state-of-the-art ML models in anomaly detection.	Hoang M. Ngo; Tre’ R. Jeter; Jung Taek Seo; My T. Thai;	arxiv-cs.LG	2026-01-16
244	A Self-supervised Acoustic Anomaly Detection Model with A Multi-branch Attention Mechanism Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, due to the scarcity and complexity of anomalous patterns, current mainstream unsupervised methods—particularly those based on autoencoders—still face significant limitations in feature extraction and modeling capacity. To address these challenges, this paper proposes an enhanced self-supervised anomaly detection framework featuring a Hierarchically Enhanced Feature Extraction Module (HEFEM), which integrates multi-path convolution and channel attention mechanisms to better capture localized anomalous patterns in industrial audio signals.	QINRUI LV et. al.	Engineering Research Express	2026-01-16
245	A Survey of Anomaly Detection in HPC Systems Using Machine Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this survey, we conduct a comprehensive and in-depth investigation of machine learning-based anomaly detection methods in HPC systems.	YIMING LU et. al.	CCF Transactions on High Performance Computing	2026-01-16
246	GFM4GA: Graph Foundation Model for Group Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: GFMs have been successfully applied to detection of individual anomalies but cannot be generalized to group anomalies, as group anomaly patterns must be detected as a whole and individuals in an abnormal group can look rather normal. Therefore, we propose GFM4GA, a novel graph foundation model for group anomaly detection.	Jiujiu Chen; Weijun Zeng; Shaofeng Hu; Sihong Xie; Hui Xiong;	arxiv-cs.AI	2026-01-15
247	Explainable Autoencoder-Based Anomaly Detection in IEC 61850 GOOSE Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes an explainable, unsupervised multi-view anomaly detection framework for IEC 61850 GOOSE networks that explicitly separates semantic integrity and temporal availability.	Dafne Lozano-Paredes; Luis Bote-Curiel; Juan Ramón Feijóo-Martínez; Ismael Gómez-Talal; José Luis Rojo-Álvarez;	arxiv-cs.CR	2026-01-14
248	3D-SONAR: Self-Organizing Network for 3D Anomaly Ranking Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, most existing methods rely on deep learning techniques that are highly dependent on large-scale datasets for training, which are difficult and expensive to acquire in real-world applications. To address this challenge, we propose a novel method based on self-organizing network for 3D anomaly ranking, also named 3D-SONAR.	Guodong Xu; Juan Du; Hui Yang;	arxiv-stat.AP	2026-01-14
249	Unsupervised Learning-Based Anomaly Detection for Bridge Structural Health Monitoring: Identifying Deviations from Normal Structural Behaviour Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Using modal frequencies extracted via Stochastic Subspace Identification from the Z24 bridge dataset, the baseline method effectively identifies structural anomalies caused by progressive damage scenarios.	JABEZ NESACKON ABRAHAM et. al.	Sensors	2026-01-14
250	Unsupervised Learning-Based Anomaly Detection for Bridge Structural Health Monitoring: Identifying Deviations from Normal Structural Behaviour Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Structural Health Monitoring (SHM) of large-scale civil infrastructure is essential to ensure safety, minimise maintenance costs, and support informed decision-making. …	JABEZ NESACKON ABRAHAM et. al.	Sensors (Basel, Switzerland)	2026-01-14
251	Data-driven Anomaly Detection for Quadcopter UAV Indoor Flight Platform Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we propose a data-driven approach for unsupervised anomaly detection in UAVs, leveraging a newly developed multimodal dataset that includes synchronized telemetry, sensor measurements, motion capture data, and pilot inputs.	Gengyu Li; Chun Fui Liew; Naoya Takeishi; Takehisa Yairi;	PHM Society Asia-Pacific Conference	2026-01-13
252	Nonlinear and Trend-Aware Industrial Time Series Anomaly Detection with Federated Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, it is hampered by the complex dynamics of time series, distributed data silos, and data heterogeneity. To overcome these challenges, we introduce a novel federated learning framework (FL) with two core modules: Multiple Definition Operators (MDO) to capture intricate temporal dynamics, and Temporal Trend Convolution (TTC) to extract interpretable trend patterns.	Zhiqing Luo; Yan Qin;	PHM Society Asia-Pacific Conference	2026-01-13
253	Study on Appearance Anomaly Detection Methods for Large-scale Nuclear Fuel Assemblies Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection of large-scale nuclear fuel assemblies is crucial for nuclear safety. Traditional manual inspection has problems such as low efficiency, strong subjectivity, and …	Chuncheng Feng; Congzheng Wang; Chang Feng;	International Symposium on Advanced Optical Manufacturing …	2026-01-13
254	A Protocol-Aware P4 Pipeline for MQTT Security and Anomaly Mitigation in Edge IoT Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a P4-based data-plane enforcement scheme for protocol-aware MQTT security and anomaly detection at the network edge.	Bui Ngoc Thanh Binh; Pham Hoai Luan; Le Vu Trung Duong; Vu Tuan Hai; Yasuhiko Nakashima;	arxiv-cs.CR	2026-01-12
255	An Online Forecasting-based Fine-tuning Pipeline for Time-series Anomaly Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save	ZHOU ZHOU et. al.	Neural networks : the official journal of the International …	2026-01-10
256	A Transformer Autoencoder-based Anomaly Detection System for Intra-vehicular Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Intra-vehicular networks (IVNs) are increasingly targeted by cyber attack disrupting the vehicular normal operation, causing damage in received data from various sensors. The …	Mostofa Fahim Hasan; Md Jahid Hasan; Md Sayem; Md Zahangir Alam; Tarem Ahmed;	International Conference on Optical and Terahertz …	2026-01-09
257	XGA-E: An Explainability-enhanced Graph Neural Network for Network Traffic Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing GNN-based approaches often lack interpretability, and their detection performance remains to be improved. To address these challenges, we propose XGA-E, an interpretability-enhanced GNN model for network traffic anomaly detection that leverages graph neural networks, explainable artificial intelligence (XAI) techniques, and gradient boosting-based anomaly detection classifiers.	Min Yang; Caiming Liu;	Cybersecurity	2026-01-09
258	Adaptive Credit Card Fraud Detection: Reinforcement Learning Agents Vs. Anomaly Detection Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study investigates two complementary approaches: anomaly detection based on multivariate normal distribution and deep reinforcement learning using a Deep Q-Network.	Houda Ben Mekhlouf; Abdellatif Moussaid; Fadoua Ghanimi;	FinTech	2026-01-09
259	Enhancing Road Safety and Sustainability: A Multi-Scale Temporal Model for Vehicle Trajectory Anomaly Detection in Road Network Interactions Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, current research faces three main challenges including scarce anomaly data, inadequate spatial feature extraction in complex road networks, and limited capability in identifying complex behaviors. To address these issues, this paper proposes a Multi-scale Temporal and Road Network Interaction Anomaly Detection model (MTRI).	Juan Chen; Haoran Chen; Hongyu Lu;	Sustainability	2026-01-07
260	Credit Card Anomaly Detection Based on Multi-Dimensionally Optimized Autoencoder Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Qin-jie Zhou;	International Journal of Science and Engineering …	2026-01-06
261	Real-Time Adaptive Anomaly Detection in Industrial IoT Environments Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose an adaptive method for detecting anomalies in IIoT streaming data utilizing a multi-source prediction model and concept drift adaptation.	Mahsa Raeiszadeh; Amin Ebrahimzadeh; Roch H. Glitho; Johan Eker; Raquel A. F. Mini;	arxiv-cs.LG	2026-01-06
262	Context-aware Anomaly Detection By Community Detection in The Internet of Things Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Fatemeh Stodt; Christoph Reich; Fabrice Theoleyre;	Computer Communications	2026-01-06
263	Anomaly Detection Method for Power Dispatch Streaming Data Based on Adaptive Isolation Forest and Self-supervised Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Methods We propose a streaming data anomaly detection method integrating adaptive isolation forests and self-supervised learning.	TENGLONG XIE et. al.	Frontiers in Physics	2026-01-06
264	Advanced Data Analytics Techniques in Fraud Detection: Anomaly Detection and Predictive Analytics Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Nrusingh Prasad Dash;	International Journal of Science and Research (IJSR)	2026-01-05
265	Multi-Task Learning for Anomaly Detection and Remaining Useful Life Prediction in Semiconductor Manufacturing Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The interactions between different tasks can lead to increased model complexity and computational overhead. This study addresses these challenges by designing a multi-task learning framework for semiconductor manufacturing systems.	Min Yin;	Journal of Computer Technology and Applied Mathematics	2026-01-05
266	Mitigating Long-Tailed Anomaly Score Distributions with Importance-Weighted Loss Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This imbalance skews model training and degrades detection performance, especially for minority instances. To address this issue, we propose a novel importance-weighted loss designed specifically for anomaly detection.	JUNGI LEE et. al.	arxiv-stat.ML	2026-01-05
267	Hunting for Oddballs with Machine Learning: Detecting Anomalous Exoplanets Using A Deep-Learned Low-Dimensional Representation of Transit Spectra with Autoencoders Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To test the performance of the different methods under realistic conditions, we introduced Gaussian noise levels ranging from 10 to 50 ppm.	ALEXANDER ROMAN et. al.	arxiv-astro-ph.EP	2026-01-05
268	A Graph-based Framework for Online Time Series Anomaly Detection Using Model Ensemble Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes GDME, an unsupervised graph-based framework for online time series anomaly detection using model ensemble.	Zewei Yu; Jianqiu Xu; Caimin Li;	arxiv-cs.LG	2026-01-04
269	A Review of Artificial Intelligence Techniques for Anomaly Detection in Smart Grid Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study provides a comprehensive overview of integrating renewable energy sources into SGs and the increasing importance of robust anomaly detection methods in ensuring grid security and reliability.	Md Al Amin Sarker; Irrai Anbu Jayaraj; Bharanidharan Shanmugam; Sami Azam; Suresh Thennadil;	Artificial Intelligence Review	2026-01-03
270	Angel or Devil: Discriminating Hard Samples and Anomaly Contaminations for Unsupervised Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	RUYI ZHANG et. al.	Neural networks : the official journal of the International …	2026-01-02
271	Hybrid Dual-Heterogeneous Knowledge Distillation Network for Anomaly Detection in Retinal OCT Images Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Moreover, the diversity of lesion types in retinal Optical Coherence Tomography (OCT) images further complicates anomaly detection. In this paper, we propose a novel hybrid dual-heterogeneous knowledge distillation network to overcome these challenges.	MUHAO XU et. al.	IEEE journal of biomedical and health informatics	2026-01-02
272	Curvature-Fused Feature Extractor for Accelerated Point Cloud Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Real-time high-precision point cloud anomaly detection faces computational bottlenecks in industrial, medical, and autonomous driving applications, where existing methods suffer …	Yujie Huang; Zhiquan Qi;	IEEE Access	2026-01-01
273	Multimodal Industrial Anomaly Detection Via Attention-Enhanced Memory-Guided Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection is a key technology in quality control for automated production lines. Currently, 2D-based anomaly detection methods fail to identify geometric structure …	Shuaibo Liu; Xiaoli Luan; Yueyang Li;	IEEE Transactions on Multimedia	2026-01-01
274	FGPT: Fine-Grained Prompt Tuning for Zero-Shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	YUEXIN WANG et. al.	IEEE Transactions on Artificial Intelligence	2026-01-01
275	SLNALog: A Log Anomaly Detection Scheme Based on Swift Layer Normalization Attention Mechanism for Next-Generation Power Communication Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Log anomaly detection is a critical first line of defense for securing next-generation power communication networks against malicious attacks. However, in industrial settings, …	Kai Cheng; Weidong Tang; Lintao Tan; Jing Yang; Jia Chen;	IEEE Transactions on Network and Service Management	2026-01-01
276	Transformer-based Anomaly Detection for Satellite Telemetry Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save	A. Fejjari; Alexis Delavault; R. Camilleri; G. Valentino;	Acta Astronautica	2026-01-01
277	A Comparative Study of Adaptation Strategies for Time Series Foundation Models in Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We explore whether time series foundation models (TSFMs), pretrained on large heterogeneous data, can serve as universal backbones for anomaly detection.	Miseon Park; Kijung Yoon;	arxiv-cs.LG	2026-01-01
278	Zoom-Anomaly: Multimodal Vision-Language Fusion Industrial Anomaly Detection with Synthetic Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Jiaqi Li; Shuhuan Wen; Hamid Reza Karimi;	Inf. Fusion	2026-01-01
279	Deviation Capture Networks for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	FENG YAN et. al.	Adv. Eng. Informatics	2026-01-01
280	Confidence-Weighted Prior-Guided RPCA for Hyperspectral Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	JINZHUANG XU et. al.	IEEE Signal Processing Letters	2026-01-01
281	Anomaly Detection for Camouflage Targets Via Hierarchical Attentional Fusion in UAV Hyperspectral Imagery Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Hyperspectral imaging (HSI) provides abundant spectral information for fine-grained target analysis, yet anomaly detection of camouflaged objects in UAV-based HSI remains …	SONG ZHAO et. al.	IEEE Journal of Selected Topics in Applied Earth …	2026-01-01
282	Toward Context-Aware Anomaly Detection for AIOps in Microservices Using Dynamic Knowledge Graphs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Microservice applications are omnipresent due to their advantages, such as scalability, flexibility and consequentially resource cost efficiency. The loosely-coupled microservices …	Pieter Moens; Bram Steenwinckel; F. Ongenae; B. Volckaert; S. V. Hoecke;	IEEE Transactions on Network and Service Management	2026-01-01
283	System Log Anomaly Detection With Noise-Contrastive Learning and Pattern Feature Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: System logs play a critical role in identifying security threats such as network attacks, unauthorized access, and system vulnerabilities. Recent research has focused on …	PENGCHENG LUO et. al.	IEEE Transactions on Network Science and Engineering	2026-01-01
284	Feasibility Study of Unsupervised Anomaly Detection Using Wasserstein GAN in SPECT Image Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In this study, we constructed an anomaly detection system based on the Wasserstein generative model in brain single-photon emission computed tomography (SPECT) images, and …	Ryosuke Kasai; Hideki Otsuka;	EJNMMI physics	2025-12-31
285	Adaptive Dynamic Thresholds for Unsupervised Joint Anomaly Detection and Trend Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To address these challenges, we propose an adaptive thresholding strategy framework for unsupervised joint anomaly detection and trend prediction. Our framework introduces a self-adaptive threshold strategy from historical data distributions and dynamically updates them in response to evolving system behavior.	FENGLIN DING et. al.	Sensors (Basel, Switzerland)	2025-12-31
286	Granularity-Inconsistent Transformer for Unsupervised Hyperspectral Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Cong Wang; Yunfeng Wang; Yu Wang; Mingming Xu; Leiquan Wang;	IEEE Journal of Selected Topics in Applied Earth …	2025-12-31
287	Real-time Multi-modal Monitoring and Anomaly Detection in Green Electricity Markets Using Visual Intelligence Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: This paper proposes the Visual Market Surveillance and Anomaly Detection Network (VMSADN), a novel algorithm designed for real-time monitoring and anomaly detection within the …	KANGPING QING et. al.	International Conference on Electronics, Electrical and …	2025-12-31
288	Atrial Fibrillation Detection Using Reservoir Computing and Anomaly Detection Method from Automated Blood Pressure Measurements Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Kentaro Takeda; Hiroyuki Kitajima; Makoto Ishizawa; Tetsuo Minamino;	Nonlinear Theory and Its Applications, IEICE	2025-12-31
289	FocusPatch AD: Few-Shot Multi-Class Anomaly Detection With Unified Keywords Patch Prompts Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Industrial few-shot anomaly detection (FSAD) requires identifying various abnormal states by leveraging as few normal samples as possible (abnormal samples are unavailable during …	Xicheng Ding; Xiaofan Li; Mingang Chen; Jingyu Gong; Yuan Xie;	IEEE transactions on image processing : a publication of …	2025-12-30
290	On Multipolar Magnetic Anomaly Detection: Multipolar Signal Subspaces, An Analytical Orthonormal Basis, Multipolar Truncation and Detection Performance Related Papers Related Patents Related Grants Related Venues Related Experts View Save	CLÉMENT CHENEVAS-PAULE et. al.	EURASIP Journal on Advances in Signal Processing	2025-12-29
291	A Unified Framework for Detecting Point and Collective Anomalies in Operating System Logs Via Collaborative Transformers Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Log anomaly detection is crucial for preserving the security of operating systems. Depending on the source of log data collection, various information is recorded in logs that can …	Mohammad Nasirzadeh; Jafar Tahmoresnezhad; Parviz Rashidi-Khazaee;	Scientific reports	2025-12-28
292	Self-discovering Temporal Anomaly Patterns in Video Anomaly Detection Via Causal Representation Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Hima Bindu Gogineni; Hemanth Kumar Bhuyan; Laxmi Lydia E;	International Journal of Information Technology	2025-12-27
293	ASOI: Anomaly Separation and Overlap Index, An Internal Evaluation Metric for Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract Evaluating unsupervised anomaly detection presents significant challenges due to the absence of ground truth labels and the complex nature of anomaly distributions.	Jiyan Salim Mahmud; Zakarya Farou; Imre Lendák;	Complex & Intelligent Systems	2025-12-26
294	High Dimensional Data Decomposition for Anomaly Detection of Textured Images Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes a texture basis integrated smooth decomposition (TBSD) approach, which is targeted at efficient anomaly detection in textured images with smooth backgrounds and sparse anomalies.	Ji Song; Xing Wang; Jianguo Wu; Xiaowei Yue;	arxiv-cs.CV	2025-12-23
295	Spatio-Temporal Graphs Beyond Grids: Benchmark for Maritime Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we introduce a novel benchmark dataset for anomaly detection in the maritime domain, extending the Open Maritime Traffic Analysis Dataset (OMTAD) into a benchmark tailored for graph-based anomaly detection.	Jeehong Kim; Youngseok Hwang; Minchan Kim; Sungho Bae; Hyunwoo Park;	arxiv-cs.LG	2025-12-23
296	Hyperbolic Graph Embeddings: A Survey and An Evaluation on Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This survey reviews hyperbolic graph embedding models, and evaluate them on anomaly detection, highlighting their advantages over Euclidean methods in capturing complex structures.	Souhail Abdelmouaiz Sadat; Mohamed Yacine Touahria Miliani; Khadidja Hab El Hames; Hamida Seba; Mohammed Haddad;	arxiv-cs.LG	2025-12-21
297	Unsupervised Anomaly Detection with An Enhanced Teacher for Student-Teacher Feature Pyramid Matching Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Anomaly detection or outlier is one of the challenging subjects in unsupervised learning . This paper is introduced a student-teacher framework for anomaly detection that its teacher network is enhanced for achieving high-performance metrics .	Mohammad Zolfaghari; Hedieh Sajedi;	arxiv-cs.CV	2025-12-20
298	Federated Sparse Representation-based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Michael Melek;	Digital Signal Processing	2025-12-19
299	Autonomous Cyber-physical Security Middleware for IoT: Anomaly Detection and Adaptive Response in Hybrid Environments Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The rapid adoption of Internet of Things (IoT) devices in cyber-physical systems introduces significant security challenges, particularly in distributed and heterogeneous …	Iván Ortiz-Garcés; William Villegas-Ch; Sergio Luján-Mora;	Frontiers in artificial intelligence	2025-12-17
300	GLBAD: Online BGP Anomaly Detection Under Partial Observation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Second, the observational data provided by current monitoring systems are inherently localized. To address these challenges, this paper proposes a Graph Learning-driven framework for BGP Anomaly Detection, named GLBAD.	Zheng Wu; Yaoyu Zhou; Junda Wu;	Electronics	2025-12-16
301	Multimode Fusion Intelligent Anomaly Detection of Rocket Telemetry Parameters Method Research Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: This paper proposes a multi-modal fusion anomaly detection method (HTMF-AD) in response to the problems that existing methods for anomaly detection in liquid rocket engine (LRE) …	Jing Yang; Jin Tong; Wenbo Wang; Sijie Xiang;	International Conference on Signal Processing and Computer …	2025-12-16
302	An Adversarial Variational Graph Autoencoder with Contrastive Learning for Robust Anomaly Detection in Large Scale Attributed Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Traditional methods rarely solve both problems simultaneously, making them less effective. We present a new approach for anomaly detection that uses adversarial variational graph autoencoders (VGAE) with attention-based residual modeling and contrastive learning to address these issues.	Wasim Khan; Nadhem Ebrahim; Mohammad Ishrat; Hasan Alkahtani; Theyazn Aldhyani;	Journal of Big Data	2025-12-14
303	Collaborative Reconstruction and Repair for Multi-class Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, under this challenging setting, conventional reconstruction-based networks often suffer from an identity mapping problem, where they directly replicate input features regardless of whether they are normal or anomalous, resulting in detection failures. To address this issue, this study proposes a novel framework termed Collaborative Reconstruction and Repair (CRR), which transforms the reconstruction to repairation.	QISHAN WANG et. al.	arxiv-cs.CV	2025-12-12
304	ICAD: A Self-Supervised Autoregressive Approach for Multi-Context Anomaly Detection in Human Mobility Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Abnormal human mobility patterns often signal disruptions, emergencies, or health-related risks, making their detection critical for applications in public safety, urban …	Bita Azarijoo; Maria Despoina Siampou; John Krumm; Cyrus Shahabi;	Proceedings of the … ACM SIGSPATIAL International …	2025-12-12
305	Energy-efficient Meta-classifier Model for Log Access Anomaly Detection in Healthcare Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes a lightweight, hybrid anomaly detection framework that integrates unsupervised, supervised and rule-based approaches using a meta-classifier architecture.	Mafalda Matos; Filipe Gomes; Fernando Nogueira; Fernando Almeida;	International Journal of Intelligent Computing and …	2025-12-11
306	Online Anomaly Detection in Correlated Datastreams Using Robust Kalman Filtering Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Taras I. Zavaliy; Nataliya B. Shakhovska;	Applied Aspects of Information Technology	2025-12-11
307	Lightweight Spectral–Spatial Attention and Tucker Decomposition for Label-Free Hyperspectral Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In these years, hyperspectral imaging has become an important component of modern remote sensing because of its capability to capture fine-grained spectral data. However, …	V. SIVA et. al.	2025 5th International Conference on Mobile Networks and …	2025-12-10
308	Anomaly Detection for Industrial Applications: Challenges, Solutions, and Future Directions Related Papers Related Patents Related Grants Related Venues Related Experts View Save	ABDELRAHMAN ALZAROONI et. al.	International Journal of Computer Integrated Manufacturing	2025-12-10
309	Attention-Based Anomaly Detection in Dynamic Network Related Papers Related Patents Related Grants Related Venues Related Experts View Save	YIMING ZHAO et. al.	Big Data Mining and Analytics	2025-12-09
310	Suspicious Activity Detection Using Surveillance Camera Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This project implements a video anomaly detection framework using YOLO to process video streams and identify unusual events in real time.	Goghul T; Prakruthi G R; Aditya Mallewadi; Akash R S; Arjun M;	International Journal of Scientific Research in Engineering …	2025-12-09
311	A Method for Anomaly Detection of Track Bed Based on Multimodal Feature Fusion Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection of track bed is critical to the safety of trains. One problem that still exists is that when using 2D images for detection, the appearance of some anomalies is …	Fenghe Yu; Yu Zhang; Yong Wang; Lin Luo; Darui Feng;	International Conference on Information Optics and Photonics	2025-12-08
312	Hyperspectral Anomaly Detection Via Hybrid Convolutional and Transformer-Based U-Net With Error Attention Mechanism Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This article proposes a novel framework using U-Net, termed hybrid convolution and transformer-based U-Net (HCT-Unet), which integrates convolution with a multihead attention mechanism in Transformer for enhanced hyperspectral anomaly detection.	XIAOYI WANG et. al.	IEEE transactions on neural networks and learning systems	2025-12-08
313	Explainable Multi-perspective Business Process Anomaly Detection Method Based on Graph Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To enable reliable detection, a multi-perspective anomaly detection and explanation method for business processes based on graph neural networks is proposed.	Wei Bao; Ke Lu; Xianwen Fang; Xiwei Zhang;	ACM Transactions on Management Information Systems	2025-12-08
314	GLAE: Global–local Feature Autoencoder for Image Logical Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	JIANJIE PENG et. al.	The Visual Computer	2025-12-08
315	Fleet-based Transfer Learning for Anomaly Detection in Industrial Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Bingsen Wang; Piero Baraldi; Enrico Zio; Jonathan Brown; Stéphane Gauthier;	Mechanical Systems and Signal Processing	2025-12-08
316	Anomaly Detection in Imbalanced Network Traffic Using A ResCAE-BiGRU Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To address the critical challenge of low detection rates for rare anomaly classes in network traffic, a problem exacerbated by severe data imbalance, this paper proposes a deep learning framework for anomaly detection in imbalanced network traffic.	Xiaofeng Nong; Kuangyu Qin; Xingliu Xie;	Symmetry	2025-12-05
317	Anomaly Detection in IoT Based Satellite Networks: NidaDeepMix Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Nida Canpolat; Sengul Dogan; Mehmet Karakose; Turker Tuncer; Musa Yenilmez;	International Journal of Wireless and Microwave Technologies	2025-12-04
318	Detection of Wire Breakage Using Unsupervised Anomaly Detection at Construction Sites Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yuichi FUJITA; Jun Younes LOUHI KASAHARA; Atsushi YAMASHITA;	Journal of the Japan Society for Precision Engineering	2025-12-04
319	Federated Learning for Anomaly Detection in Maritime Movement Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces M3fed, a novel solution for federated learning of movement anomaly detection models.	Anita Graser; Axel Weißenfeld; Clemens Heistracher; Melitta Dragaschnig; Peter Widhalm;	arxiv-cs.LG	2025-12-04
320	Optimal Transport Event Representation for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce optimal transport (OT) as a physics-based intermediate event representation for weakly supervised anomaly detection.	Aditya Bhargava; Tianji Cai; Benjamin Nachman;	arxiv-hep-ph	2025-12-04
321	Contra-Discriminative GAN-based Anomaly Detection Framework for Medical Images Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce a novel Contra-Discriminative GAN (CD-GAN) that utilizes unlabeled images to guide the generation process.	TIANZE YU et. al.	Annual International Conference of the IEEE Engineering in …	2025-12-03
322	Combined Anomaly Features and Interictal Epileptiform Discharges for Effective Seizure Onset Zone Localization Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes the application of autoencoder-based anomaly detection in SOZ electrode classification for the first time.	Nawara Mahmood Broti; Masaki Iwasaki; Yumie Ono;	Annual International Conference of the IEEE Engineering in …	2025-12-03
323	Real-time Anomaly Detection in IoT Streams Through Spatiotemporal Patterns Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yazeed AlZahrani;	Discover Internet of Things	2025-12-03
324	TinyML-based OOD Anomaly Detection and Time Synchronization Optimization: Enhancing The Spatiotemporal Consistency of Anomalous Data in Industrial IoT Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Purpose This study aim to propose a low-power, edge-deployable out-of-distribution (OOD) anomaly detection model and an anomaly-triggered time synchronization mechanism to address the challenges of anomaly detection accuracy and spatiotemporal consistency in Industrial Internet of Things (IIoT) systems, particularly for resource-constrained TinyML platforms.	Min Wang; Weihao Bian; Qin Xie; Mingxing Lv; Qifei Du;	Sensor Review	2025-12-02
325	AI-Driven Anomaly Detection in Cloud-Native Microservices: The Night’s Watch Algorithm Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces the Night’s Watch algorithm, a novel unsupervised method for detecting anomalies in microservices.	GHAITH DKMAK et. al.	Applied Sciences	2025-12-02
326	Community-aware Multi-granularity Contrastive Learning for Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	PANPAN MENG et. al.	Expert Syst. Appl.	2025-12-01
327	Anomaly Detection Based on Markovian Geometric Diffusion Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes an unsupervised anomaly-detection method called Anomaly Detection Based on Markovian Geometric Diffusion (AD-MGD).	Erikson Carlos Ramos; Leandro Carlos de Souza; Gustavo Henrique Matos Bezerra Motta;	Machine Learning and Knowledge Extraction	2025-12-01
328	A Coattention Enhanced Multimodal Feature Fusion With Inner Feature for Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Current anomaly detection methods struggle with the nonlinear, dynamic, and multisource nature of industrial processes. This article proposes a novel end-to-end architecture with …	Danwei Zhang; Hongshuo Sun; Wen Yu; Quan Xu; Tianyou Chai;	IEEE/ASME Transactions on Mechatronics	2025-12-01
329	Elevating Datacenter Resilience with ThermADNet: A Thermal Anomaly Detection System Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Mohsen Seyedkazemi Ardebili; A. Acquaviva; Luca Benini; Andrea Bartolini;	Future Gener. Comput. Syst.	2025-12-01
330	Hybrid Smoothing for Anomaly Detection in Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Matthew Hofkes; Douglas Nychka; Tzahi Y. Cath; Amanda S. Hering; Craig McGonagill;	Technometrics	2025-12-01
331	Winning Solutions for The Rayan AI Contest: Compositional Retrieval, Zero-Shot Anomaly Detection, and Backdoor Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This report presents solutions to three machine learning challenges: compositional image retrieval, zero-shot anomaly detection, and backdoored model detection.	Ali Nafisi; Sina Asghari; Mohammad Saeed Arvenaghi; Hossein Shakibania;	arxiv-cs.LG	2025-12-01
332	MoBA: Motion Memory-augmented Deblurring Autoencoder for Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	JIAHAO LYU et. al.	Knowl. Based Syst.	2025-12-01
333	Fine-grained Multivariate Time Series Anomaly Detection Via Causal Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Xiangwei Chen; Hancheng Xiao; Zhixia Zeng; Shi Zhang; Ruliang Xiao;	Knowl. Based Syst.	2025-12-01
334	L-PromptCTRL: Learnable Prompting for Contextual Residual Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Minmin Zhou; Ying Chen; Shunyuan Sun;	Digit. Signal Process.	2025-12-01
335	Accurate Industrial Anomaly Detection with Efficient Multimodal Fusion Related Papers Related Patents Related Grants Related Venues Related Experts View Save	DINH-CUONG HOANG et. al.	Array	2025-12-01
336	A Review of Deep Learning Based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	YAXIN SHI et. al.	Neurocomputing	2025-12-01
337	Anomaly Detection Method of Maglev Train Suspension System Based on SSA–MLP–Attention Hybrid Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection of the maglev train suspension system is crucial for the train’s safe operation and maintenance. In order to solve the complexity and diversity of abnormality …	Hongxin Che; Biao Yang; Zhiqiang Long; Zhuang Ma;	IEEE Transactions on Transportation Electrification	2025-12-01
338	A Framework for Process Anomaly Detection in 3D Concrete Printing Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Abdallah Kamhawi; Yuxin Lin; Christopher Watson; K. Barton; Mania Aghaei Meibodi;	Additive Manufacturing	2025-12-01
339	Enhancing Weakly Supervised Video Anomaly Detection with Object-Centric Features Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Surveillance cameras are extensively deployed across public and private environments, driving the need for intelligent video monitoring systems. However, a major challenge arises …	Yanyu Wang; Yang Chen; Chai Kiat Yeo;	Inf.	2025-11-30
340	AF-TAD: Transformer-Based Anomaly Detection for Aircraft Fuel Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: This paper presents AF-TAD, which stands for Aircraft Fuel Transformer Anomaly Detection, a Transformer-based reconstruction model specifically designed for time-series anomaly …	Xulang Ouyang; Yanqiang Zhang; Lu Hua; Yongfeng Yin;	Aerospace	2025-11-30
341	SD-CGAN: Conditional Sinkhorn Divergence GAN for DDoS Anomaly Detection in IoT Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes SD-CGAN, a Conditional Generative Adversarial Network framework enhanced with Sinkhorn Divergence, tailored for robust anomaly detection in IoT edge environments.	HENRY ONYEKA et. al.	arxiv-cs.LG	2025-11-28
342	Semantic-aware Reinforcement and Ensemble Learning for Signal Management and Anomaly Detection in IoT Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a semantic-aware hybrid framework that integrates deep reinforcement learning (DRL) and random forest (RF) classification for intelligent signal optimization and anomaly detection.	Samad Wali; Muhammad Irfan Khan; Mudassar Imran;	Scientific reports	2025-11-28
343	A Fast Collaborative Representation Algorithm Based on Extended Multi-Attribute Profiles for Hyperspectral Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: As one of the vital research directions in hyperspectral image (HSI) processing, anomaly detection is dedicated to identifying anomalous pixels in HSIs that have significant …	FANG HE et. al.	Remote Sensing	2025-11-28
344	Efficient Lightweight Privacy Data Anomaly Detection Solution with Robust Aggregation Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Jiateng Zhao; Bin Wen; Jiashuai Yang; Shang Zhou;	Scientific Reports	2025-11-27
345	AnoRefiner: Anomaly-Aware Group-Wise Refinement for Zero-Shot Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We observe that anomaly score maps exactly provide complementary spatial cues that are largely absent from ZSAD’s image features, a fact overlooked before. Inspired by this, we propose an anomaly-aware refiner (AnoRefiner) that can be plugged into most ZSAD models and improve patch-level anomaly maps to the pixel level.	Dayou Huang; Feng Xue; Xurui Li; Yu Zhou;	arxiv-cs.CV	2025-11-27
346	ARES: Anomaly Recognition Model For Edge Streams Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Unlike traditional anomaly detection, this task is particularly challenging due to concept drifts, large data volumes, and the need for real-time response. To face these challenges, we introduce ARES, an unsupervised anomaly detection framework for edge streams.	Simone Mungari; Albert Bifet; Giuseppe Manco; Bernhard Pfahringer;	arxiv-cs.LG	2025-11-26
347	ADNet: A Large-Scale and Extensible Multi-Domain Benchmark for Anomaly Detection Across 380 Real-World Categories Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce ADNet, a large-scale, multi-domain benchmark comprising 380 categories aggregated from 49 publicly available datasets across Electronics, Industry, Agrifood, Infrastructure, and Medical domains.	HAI LING et. al.	arxiv-cs.CV	2025-11-25
348	Structural-temporal Coupling Anomaly Detection with Dynamic Graph Transformer Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save	Chang Zong; Yueting Zhuang; Jian Shao; Weiming Lu;	Data Mining and Knowledge Discovery	2025-11-24
349	Optimizing Temporal Features for Anomaly Detection in Smart Grids Related Papers Related Patents Related Grants Related Venues Related Experts View Save	BELAWAL BEHRAM et. al.	Electric Power Systems Research	2025-11-24
350	Attention-Driven Deep Learning Framework for Intelligent Anomaly Detection in ETL Processes IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: This paper addresses the problem of anomaly detection in multi-source heterogeneous data within the ETL (Extract-Transform-Load) process and proposes an intelligent detection …	Cong Nie; Haige Wang; Chifu Chiang;	2025 6th International Symposium on Computer Engineering …	2025-11-24
351	Enhancing Anomaly Detection with Topology-aware Autoencoders Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work explores topology-aware autoencoders, embedding phase-space distributions onto compact manifolds that reflect energy-momentum conservation.	Vishal S Ngairangbam; Błażej Rozwoda; Kazuki Sakurai; Michael Spannowsky;	Machine Learning: Science and Technology	2025-11-24
352	Trend Factor Smoothing and Tasmanian Devil Optimization Based Siamese Neural Network for Anomaly Detection in Predictive Maintenance Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The proposed TFsTDO-SNN system encompasses preprocessing through Box-Cox transformation, feature selection utilizing an innovative TFsTDO algorithm, anomaly injection via oversampling, and anomaly detection employing an SNN trained by TFsTDO.	Ida Hector; Rukmani Panjanathan;	Scientific reports	2025-11-24
353	ZAAS: Zonal Aware Anomaly Score for Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a Zone Normalized F1, which treats each true and each predicted anomaly interval as a unit, macro‑averaging precision and recall over intervals rather than windows.	Nabil Ait Said; Elies Gherbi; Faouzi Adjed; Achraf Kallel;	Proceedings of the AAAI Symposium Series	2025-11-23
354	Evaluating Uncertainty in Deep Q-Network Ensembles for Trustworthy Anomaly Detection in Medical Imaging Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study establishes the foundation for uncertainty-aware, reinforcement learning–based anomaly detection models that enhance reliability, interpretability, and clinical usability in large-scale MRI analysis.	Zeduo Zhang; Yalda Mohsenzadeh;	Proceedings of the AAAI Symposium Series	2025-11-23
355	Multimodal Real-Time Anomaly Detection and Industrial Applications Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents the design, implementation, and evolution of a comprehensive multimodal room-monitoring system that integrates synchronized video and audio processing for real-time activity recognition and anomaly detection.	Aman Verma; Keshav Samdani; Mohd. Samiuddin Shafi;	arxiv-cs.SD	2025-11-23
356	Real-Time Anomaly Detection in Smart Grids,Industrial IOT,Autonomous Vehicles Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The model is deployed on edge devices for low-latency processing and uses a multi-stream data fusion mechanism to analyze sensor,communication, and control signals simultaneously.Experimental simulations across smart grid load datasets, IIoT factory sensor datasets,and vehicular CAN-bus datasets show detection accuracies of 96.4%, 94.8%, and 97.1%,respectively.The proposed solution demonstrates superior performance in terms of detection speed, false-positive rate, and adaptability compared to traditional systems, making it suitable for high-reliability real-time environments.	Suhas Bhimrao Veer;	International Journal of Scientific Research in Engineering …	2025-11-22
357	Lightweight Autoencoder-Isolation Forest Anomaly Detection for Green IoT Edge Gateways Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents \textit{EcoDefender}, a sustainable hybrid anomaly detection framework that integrates \textit{Autoencoder(AE)}-based representation learning with \textit{Isolation Forest(IF)} anomaly scoring.	Saeid Jamshidi; Fatemeh Erfan; Omar Abdul-Wahab; Martine Bellaiche; Foutse Khomh;	arxiv-cs.CR	2025-11-22
358	Scalable Anomaly Detection in Cloud Logs with Sparse Transformer Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Log anomaly detection plays a crucial role in the analysis of cloud log files by identifying irregular log entries that may signify system faults or security breaches. With the …	Anu V.R.;	2025 IEEE Recent Advances in Intelligent Computational …	2025-11-20
359	Vessel Trajectory Anomaly Detection Based on Multi-scale Convolutional Autoencoder Related Papers Related Patents Related Grants Related Venues Related Experts View Save	YUHAO QI et. al.	Ocean Engineering	2025-11-20
360	SNAP Framework: Linked Prediction Based Anomaly Prevention With Suspicious Nodes on Social Network Graph Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, a Suspicious Nodes Anomaly Prevention framework for anomaly prevention has been developed.	Vahide Nida Kılıç; Esra Saraç Eşsiz;	JUCS – Journal of Universal Computer Science	2025-11-20
361	Causal Deep Learning for Enhancing Explainability in 6G Network Edge Intelligence Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work establishes a new cybersecurity paradigm for 6G edge intelligence through causal reasoning.	XIAO YI et. al.	Scientific reports	2025-11-19
362	Memory Bank-guided Diffusion Model for Lightweight Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Woojun Lee; Pilsung Kang;	Applied Soft Computing	2025-11-19
363	Hybrid Arithmetic Optimization Algorithm for Telecom Network Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Abdulle Hassan Mohamud;	Scientific Reports	2025-11-18
364	ANOMALIES DETECTION AND TRAFFIC MONITORING SYSTEM IN COMPUTER NETWORKS Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The paper addresses the problem of anomaly detection in network traffic and proposes a comprehensive solution to enhance the level of cybersecurity for organizations of various scales.	O.V. Khoma; I.Yu. Yurchak; A.O. Khich;	Computer systems and network	2025-11-18
365	Real‐time Anomaly Detection in Construction Equipment Operations Using Unsupervised Audio Signal Processing Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes a novel unsupervised audio signal processing framework for real‐time monitoring of construction equipment based on their operational acoustic signatures.	Hojat Behrooz; Mohammad Ilbeigi; Abbas Rashidi;	Computer-Aided Civil and Infrastructure Engineering	2025-11-18
366	Fourier-KAN-Mamba: A Novel State-Space Equation Approach for Time-Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose Fourier-KAN-Mamba, a novel hybrid architecture that integrates Fourier layer, Kolmogorov-Arnold Networks (KAN), and Mamba selective state-space model.	Xiancheng Wang; Lin Wang; Rui Wang; Zhibo Zhang; Minghang Zhao;	arxiv-cs.LG	2025-11-18
367	How to Pick The Best Anomaly Detector? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce the data-driven ARGOS metric, which has a sound theoretical foundation and is empirically shown to robustly select the most sensitive anomaly detection model given the data.	MARIE HEIN et. al.	arxiv-hep-ph	2025-11-18
368	Video-Based Traffic Anomaly Detection with Vision-Language Models: A Survey Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Traffic anomaly detection is a hot research topic in road safety. With the rapid growth of video data, Video-based Traffic Anomaly Detection (VTAD) becomes a core module in safe …	Yuxin Zheng; Wei Zhou; S. Nastic; Chen Wang;	2025 IEEE 28th International Conference on Intelligent …	2025-11-18
369	EGDN-KL: Dynamic Graph-deviation Network for EEG Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Ilyes Naidji; Ahmed Tibermacine; Imad Eddine Tibermacine; Samuele Russo; Christian Napoli;	Biomed. Signal Process. Control.
370	LLM-Powered Text-Attributed Graph Anomaly Detection Via Retrieval-Augmented Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we introduce TAG-AD, a comprehensive benchmark for anomaly node detection on TAGs.	HAOYAN XU et. al.	arxiv-cs.LG	2025-11-16
371	ProtoAnomalyNCD: Prototype Learning for Multi-class Novel Anomaly Discovery in Industrial Scenarios Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Since industrial anomalies are semantically subtle and current methods do not sufficiently exploit image priors, direct clustering approaches often perform poorly. To address these challenges, we propose ProtoAnomalyNCD, a prototype-learning-based framework for discovering unseen anomaly classes of multiple types that can be integrated with various anomaly detection methods.	Botong Zhao; Qijun Shi; Shujing Lyu; Yue Lu;	arxiv-cs.CV	2025-11-16
372	Ensuring Secure Conversational Commerce: Anomaly Detection in Chatbot Interactions Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Amardeep Kumar; Danish Ali Khan; Ruhul Amin;	Expert Syst. Appl.
373	Robust Anomaly Detection Through Multi-modal Autoencoder Fusion for Small Vehicle Damage Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Sara Khan; Mehmed Yüksel; Frank Kirchner;	Machine Learning with Applications	2025-11-15
374	CEDL: Centre-Enhanced Discriminative Learning for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To achieve unified learning of geometric normality and label discrimination, we propose Centre-Enhanced Discriminative Learning (CEDL), a novel supervised anomaly detection framework that embeds geometric normality directly into the discriminative objective.	ZAHRA ZAMANZADEH DARBAN et. al.	arxiv-cs.LG	2025-11-15
375	Differentially Private Upsampling for Enhanced Anomaly Detection in Imbalanced Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yujin Choi; Jinseong Park; Youngjoo Park; Jaewook Lee; Junyoung Byun;	Engineering Applications of Artificial Intelligence	2025-11-15
376	A Time Series Anomaly Detection Method Integrating GAN and GRU Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Time series anomaly detection is crucial in practical applications such as sensor data monitoring, financial market analysis, and industrial control systems. Traditional methods …	Hailong Zhang; Xiuying Li;	International Workshop on Automation, Control, and …	2025-11-14
377	Real-Time Risk Control Effects of Digital Compliance Dashboards: An Empirical Study Across Multiple Enterprises Using Process Mining, Anomaly Detection, and Interrupt Time Series Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Based on 34 cross-border project logs (ERP/work orders/approval flows) from 2018 to 2023 at Aiku Communications and multiple multinational corporations, this study employs process …	Weijun Zhu; Yao Yao; Jingwen Yang;	Proceedings of the 2025 International conference on …	2025-11-14
378	Semantic Anchor-Aligned Model for Interpretable Video Anomaly Detection Under Cross-Modal Weak Supervision Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Weakly supervised video anomaly detection is a key technique that relies solely on video-level labels to identify anomalous events. However, traditional multiple instance learning …	Weishan Gao; Jiangang Wang; Ye Wang; Xiaoyin Wang; Xiaochuan Jing;	Journal of visualized experiments : JoVE	2025-11-14
379	A Visual Dataset for Anomaly Detection in Self-Driving Laboratories Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Self-driving laboratories accelerate the application of the scientific method and the discovery process through high-throughput experimentation, intelligent perception and …	SHIWEI LIN et. al.	Scientific data	2025-11-14
380	Explainable Deep Convolutional Multi-Type Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose MultiTypeFCDD, a simple and lightweight convolutional framework designed as a practical alternative for explainable multi-type anomaly detection.	Alex George; Lyudmila Mihaylova; Sean Anderson;	arxiv-cs.CV	2025-11-14
381	A Multimodal Alignment-Based Anomaly Detection Method for Bankruptcy Prediction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: We present a novel anomaly detection method for next-year bankruptcy prediction, utilizing a combination of financial figures and textual content from annual reports. Our …	Andreas Sideras; K. Bougiatiotis; Elias Zavitsanos; Georgios Paliouras; George Vouros;	Proceedings of the 6th ACM International Conference on AI …	2025-11-14
382	Industrial Anomaly Detection Based on Improved Diffusion Model: A Review Related Papers Related Patents Related Grants Related Venues Related Experts View Save	JIAHUI WANG et. al.	Cognitive Computation	2025-11-13
383	Real-Time Crime Insights: Anomaly Detection Using Machine Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Akshitha B R Ravindra Prasad; Chithra Shree G C Archana; Deepthi P B;	IJARCCE	2025-11-13
384	Interpretable Contrastive Learning for Robust and Explainable Anomaly Detection in Financial and Organizational Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose an interpretable contrastive learning framework for robust and explainable anomaly detection.	Jianti Zheng; Wenyan Qiu; Shiwang Huang;	International Journal of Pattern Recognition and Artificial …	2025-11-12
385	Adaptive Hierarchical Attention for Multivariate Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Xiaohan You; Xiaobo Guo; Binfeng Wang; Changbin Wang;	Annals of Data Science	2025-11-12
386	MSAF-AD: Industrial Anomaly Detection Based on Multi-scale Anomaly Synthesis and Adaptive Feature Fusion Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Lanxiao Li; Chuanxu Wang; Qingyang Yang; Yishuo Liu; Jiawei Li;	Journal of Electronic Imaging	2025-11-11
387	AnDri: A System for Anomaly and Drift Co-Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Differentiating between concept drift and anomalies is critical for accurate analysis as studies have shown that the compounding effects of error propagation in downstream data analysis tasks lead to lower detection accuracy and increased overhead due to unnecessary model updates.	Jongjun Park; Ziqi Guo; Fei Chiang;	cikm	2025-11-10
388	FreeGAD: A Training-Free Yet Effective Approach for Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Surprisingly, our empirical findings suggest that the training phase of deep GAD methods, commonly perceived as crucial, may actually contribute less to anomaly detection performance than expected. Inspired by this, we propose FreeGAD, a novel training-free yet effective GAD method.	YUNFENG ZHAO et. al.	cikm	2025-11-10
389	MetaCAN: Improving Generalizability of Few-shot Anomaly Detection with Meta-learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Existing methods try to enhance the generalizability of AD by incorporating large vision-language models (LVLMs).	ZHISHENG LV et. al.	cikm	2025-11-10
390	RobustA: Robust Anomaly Detection in Multimodal Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To streamline this work, we propose RobustA, a carefullycurated evaluation dataset to systematically observe the impacts of audio andvisual corruptions on the overall effectiveness of anomaly detection systems.Furthermore, we propose a multimodal anomaly detection method, which showsnotable resilience against corrupted modalities.	SALEM ALMARRI et. al.	arxiv-cs.LG	2025-11-10
391	AI on The Pulse: Real-Time Health Anomaly Detection with Wearable and Ambient Intelligence Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce AI on the Pulse, a real-world-ready anomaly detection system that continuously monitors patients using a fusion of wearable sensors, ambient intelligence, and advanced AI models.	Davide Gabrielli; Bardh Prenkaj; Paola Velardi; Stefano Faralli;	cikm	2025-11-10
392	Real Time Ransomware Detection in Cloud VMS Using Behavioral Biometrics Homomorphic Encryption and GMM Based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Haitham A. Mahmoud; Abdelaty Edrees Abdelgawad; Ahmed T. Soliman; Mohammed A. El-Meligy;	International Journal of Information Security	2025-11-10
393	ANOMALY DETECTION IN IOT NETWORKS USING AI MACHINE LEARNING AND STATISTICAL MODELS Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The explosive growth of the Internet of Things (IoT) has significantly expanded the attack surface across modern digital ecosystems, making efficient and accurate anomaly …	V. Katta; Ravindra B. Gadhiya; Mrs. Iffat Habib; P. Patavardhan;	International Journal of Applied Mathematics	2025-11-09
394	UniADC: A Unified Framework for Anomaly Detection and Classification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce the task of unified anomaly detection andclassification, which aims to simultaneously detect anomalous regions in imagesand identify their specific categories.	Ximiao Zhang; Min Xu; Zheng Zhang; Junlin Hu; Xiuzhuang Zhou;	arxiv-cs.CV	2025-11-09
395	ZeroLog: Zero-Label Generalizable Cross-System Log-based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we take astep forward and study a valuable yet underexplored setting: zero-labelcross-system log-based anomaly detection, that is, no labeled logs areavailable in the target system.	Xinlong Zhao; Tong Jia; Minghua He; Ying Li; Gang Huang;	arxiv-cs.SE	2025-11-08
396	An Anomaly Detection Method for Conformal Mechanism Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Jian Zheng; Jingjing Sun; Qiankun Liao; Mengyun Xie; Shengye Wang;	Egyptian Informatics Journal	2025-11-08
397	Kunlun Anomaly Troubleshooter: Enabling Kernel-Level Anomaly Detection and Causal Reasoning for Large Model Distributed Inference Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce KunlunAnomaly Troubleshooter (KAT), the first anomaly troubleshooting frameworktailored for LMDI.	YUYANG LIU et. al.	arxiv-cs.LG	2025-11-08
398	Fairness-aware Anomaly Detection Via Fair Projection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Experiments on real-world benchmarks demonstrate that our method achieves an improved trade-off between detection accuracy and fairness under both balanced and skewed data across different groups.	Feng Xiao; Xiaoying Tang; Jicong Fan;	nips	2025-11-07
399	ScatterAD: Temporal-Topological Scattering Mechanism for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we conduct an empirical analysis showing that both normal and anomalous samples tend to scatter in high-dimensional space, especially anomalous samples are markedly more dispersed.	TAO YIN et. al.	nips	2025-11-07
400	Generalizing Single-Frame Supervision to Event-Level Understanding for Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To address these limitations, we propose a novel paradigm: Single-Frame supervised VAD (SF-VAD), which uses a single annotated abnormal frame per abnormal video.To validate its effectiveness, we construct three SF-VAD benchmarks by manually re-annotating the ShanghaiTech, UCF-Crime, and XD-Violence datasets in a practical procedure.	JUNXI CHEN et. al.	nips	2025-11-07
401	PANDA: Towards Generalist Video Anomaly Detection Via Agentic AI Engineer Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose PANDA, an agentic AI engineer based on MLLMs.	Zhiwei Yang; Chen Gao; Mike Zheng Shou;	nips	2025-11-07
402	BLADE: Behavior-Level Anomaly Detection Using Network Traffic in Web Services Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Existing traffic anomaly detection approaches focus onflow-level attacks, yet fail to recognize behavior-level attacks, which appearbenign in individual flows but reveal malicious purpose using multiple networkflows. To transcend this limitation, we propose a novel unsupervised trafficanomaly detection system, BLADE, capable of detecting not only flow-level butalso behavior-level attacks in web services.	Zhibo Dong; Yong Huang; Shubao Sun; Wentao Cui; Zhihua Wang;	arxiv-cs.CR	2025-11-07
403	Normal-Abnormal Guided Generalist Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Previous GAD methods primarily use only normal samples as references, overlooking the valuable information contained in anomalous samples that are often available in real-world scenarios. To address this limitation, we propose a more practical approach: normal-abnormal-guided generalist anomaly detection, which leverages both normal and anomalous samples as references to guide anomaly detection across diverse domains.	Yuexin Wang; Xiaolei Wang; Yizheng Gong; Jimin XIAO;	nips	2025-11-07
404	A Unified Reasoning Framework for Holistic Zero-Shot Video Anomaly Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a unified reasoning framework that bridges the gap between temporal detection, spatial localization, and textual explanation.	DONGHENG LIN et. al.	nips	2025-11-07
405	Registration Is A Powerful Rotation-Invariance Learner for 3D Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To this end, we propose a registration-induced, rotation-invariant feature extraction framework that integrates the objectives of point-cloud registration and memory-based anomaly detection.	YUYANG YU et. al.	nips	2025-11-07
406	Self-Perturbed Anomaly-Aware Graph Dynamics for Multivariate Time-Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Detecting anomalies in multivariate time-series data is an essential task across various domains, yet there are unresolved challenges such as (1) severe class imbalance between normal and anomalous data due to rare anomaly availability in the real world; (2) limited adaptability of the static graph-based methods to dynamically changing inter-variable correlations; and (3) neglect of subtle anomalies due to overfitting to normal patterns in reconstruction-based methods. To tackle these issues, we propose Self-Perturbed Anomaly-Aware Graph Dynamics (SPAGD), a framework for time-series anomaly detection.	JINYU CAI et. al.	nips	2025-11-07
407	A Feedback-driven Anomaly Detection Framework for Smart Homes: An Anomaly-enhanced Activity Recognition Iteration (AEARI) Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Khalid Aziz; Sakshi Dua; Prabal Gupta;	Journal of Ambient Intelligence and Humanized Computing	2025-11-06
408	When Correlation Becomes Causation: Deep Learning for Complex Anomaly Detection in Semiconductor Yield Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: We present an explainable anomaly detection framework for semiconductor photomask manufacturing data, designed to identify and interpret complex abnormal patterns in multivariate …	Jungwook Shon; Simon S. Woo;	Photomask Technology	2025-11-06
409	Graph Neural AI with Temporal Dynamics for Comprehensive Anomaly Detection in Microservices Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study addresses the problem of anomaly detection and root cause tracingin microservice architectures and proposes a unified framework that combinesgraph neural networks with temporal modeling.	QINGYUAN ZHANG et. al.	arxiv-cs.LG	2025-11-05
410	Video Anomaly Detection for Generalization and Semantic Understanding Method Evolution and Future Directions Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Abnormal user behavior may indicate health risks or security threats. Timely detection of such behavior is crucial in smart cities, healthcare monitoring, and public safety. In …	Xiaowei Chen;	International Conference on Image Processing, Intelligent …	2025-11-04
411	Unsupervised Anomaly Detection for Critical Components in Industrial Manufacturing Via Multistage Clustering Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: To address the challenges of confidentiality in industrial field data and the scarcity of labeled samples, this study proposes an unsupervised fault diagnosis framework that …	JICHEN ZHANG et. al.	International Conference on Image Processing, Intelligent …	2025-11-04
412	ANOMALY DETECTION FRAMEWORKS TAXONOMY Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This research introduces a taxonomy of anomaly detection frameworks, focusing on their capabilities, design dimensions, and levels of abstraction.	Imelda Zadeja; Kaspars Osis;	SOCIETY. TECHNOLOGY. SOLUTIONS. Proceedings of the …	2025-11-04
413	UniAD: A Real-World Multi-Category Industrial Anomaly Detection Dataset with A Unified CLIP-Based Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: These approaches require separate models for each product type and fail to model the complex multi-modal distribution of normal samples in multi-category scenarios. To overcome these limitations, we propose UniCLIP-AD, a unified anomaly detection framework that leverages the general semantic knowledge of CLIP and adapts it to the industrial domain using Low-Rank Adaptation (LoRA).	Junyang Yang; Jiuxin Cao; Chengge Duan;	Information	2025-11-04
414	An Open-Access Benchmark of Statistical and Machine-Learning Anomaly Detection Methods for Battery Applications Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we present OSBAD as anopen-source benchmark for anomaly detection frameworks in battery applications.By benchmarking 15 diverse algorithms encompassing statistical, distance-based,and unsupervised machine-learning methods, OSBAD enables a systematiccomparison of anomaly detection methods across heterogeneous datasets.	Mei-Chin Pang; Suraj Adhikari; Takuma Kasahara; Nagihiro Haba; Saneyuki Ohno;	arxiv-cs.LG	2025-11-03
415	ICAD: A Self-Supervised Autoregressive Approach for Multi-Context Anomaly Detection in Human Mobility Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Abnormal human mobility patterns often signal disruptions, emergencies, or health-related risks, making their detection critical for applications in public safety, urban …	Bita Azarijoo; M. Siampou; John Krumm; Cyrus Shahabi;	Proceedings of the 33rd ACM International Conference on …	2025-11-03
416	Uncertainty-aware Spatio-Temporal Human Mobility Modeling and Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Given the temporal GPS coordinates from a large set of human agents, how can we model their mobility behavior toward effective anomaly (e.g., bad-actor or malicious behavior) …	Haomin Wen; Shurui Cao; Zeeshan Rasheed; Khurram Shafique; L. Akoglu;	Proceedings of the 33rd ACM International Conference on …	2025-11-03
417	System Log Anomaly Detection Based on Contrastive Learning and Retrieval Augmented Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In the inference phase, a retrieval-augmented method based on KNN is introduced.	WEIAN LI et. al.	Scientific reports	2025-11-03
418	Deep Anomaly Detection for Time Series: A Survey Related Papers Related Patents Related Grants Related Venues Related Experts View Save	XUDONG JIA et. al.	Comput. Sci. Rev.	2025-11-01
419	Toward Robust Video Anomaly Detection in 6G Networks: A Scene-Adaptive Framework Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the rapid advancement of 5th Generation (5G) networks, their low latency and high bandwidth facilitate the development of smart city systems. Among the smart city systems, …	Sijia Zhang; Yong Yu; Xiaoling Tao; Lianhai Wang;	IEEE Network	2025-11-01
420	An Anomaly Detection Approach for Maglev Trains’ Levitation System With Weighted Correlation Coefficient and Minimum Distance Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The levitation system is a critical component of maglev trains, yet it is susceptible to abnormalities such as guideway settlement, fixture loosening, and component aging, which …	Biao Yang; Cuicui Huang; Zhiqiang Long;	IEEE Sensors Journal	2025-11-01
421	Anomaly Detection in Heterogeneous Cybersecurity Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save	S. Okolie; C. Amadi; J. N. Odii; E. C. Nwokorie; U. C. Onyemauche;	Franklin Open	2025-11-01
422	Reconstruction-based Distillation for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Mengyang Zhao; Qiang Guo;	Comput. Graph.	2025-11-01
423	Real-IAD Variety: Pushing Industrial Anomaly Detection Dataset to A Modern Era Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Current datasets exhibitrestricted category diversity and insufficient scale, frequently resulting inmetric saturation and limited model transferability to real-world scenarios. Toaddress this gap, we introduce Real-IAD Variety, the largest and most diverseIAD benchmark, comprising 198,960 high-resolution images across 160 distinctobject categories.	WENBING ZHU et. al.	arxiv-cs.CV	2025-11-01
424	Text-guided Fine-Grained Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose Text-guidedFine-Grained Video Anomaly Detection (T-VAD), a framework built upon LargeVision-Language Model (LVLM).	Jihao Gu; Kun Li; He Wang; Kaan Akşit;	arxiv-cs.CV	2025-11-01
425	MADFlow: Multimodal Difference Compensation Flow for Multimodal Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	YAO LI et. al.	Neurocomputing	2025-11-01
426	Anomaly Detection in Unmanned Aerial Vehicles Flight Data: A Survey Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Ahad Ghasemi; Ali Ghaffari; Nahideh Derakhshanfard; Nadir Ibrahimoglu; Amir Pakmehr;	Ad Hoc Networks	2025-11-01
427	LSH-GANSAD: A Spectrum Anomaly Detection Model Based on Local Sensitive Hashing and Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Spectrum anomaly detection is critical for ensuring the security of wireless communications. However, traditional spectrum and time-series analysis models often suffer from the …	An Chen;	Journal of Physics: Conference Series	2025-11-01
428	Visual Anomaly Detection Algorithms: Development and Frontier Review Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Jia Huang; Wei Quan; Xiwen Li;	J. Vis. Commun. Image Represent.	2025-11-01
429	Multimodal Feature Cooperative Refinement for Few-shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	LUO XU et. al.	Adv. Eng. Informatics	2025-11-01
430	MP-DRA: Multi-scale Memory and Adaptive Pseudo-anomaly Enhanced Open-set Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yunxue Shao; Fangdi Xu; Lingfeng Wang;	Neurocomputing	2025-11-01
431	XGBoost-LR: A Method for Network Traffic Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	TIANYU LIU et. al.	International Journal of Cognitive Computing in Engineering	2025-11-01
432	An Online Anomaly Monitoring Method Based on Multiscale Spatiotemporal Graph Learning for Wind Turbine Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The variation in multivariate time series (MTS) under wind turbine (WT) operational conditions makes it challenging for traditional anomaly detection methods to model expected …	Qing Xu; Dazhong Ma; Haorao Zhao; Qiuye Sun;	IEEE Transactions on Industrial Informatics	2025-11-01
433	Edge-assisted Framework for Instant Anomaly Detection and Cloud-based Anomaly Recognition in Smart Surveillance IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Adnan Hussain; Noman Khan; Zulfiqar Ahmad Khan; Hikmat Yar; Sung Wook Baik;	Eng. Appl. Artif. Intell.	2025-11-01
434	Lightweight Transformer-based Generative Adversarial Network for Acoustic Anomaly Detection in Converter Valves Related Papers Related Patents Related Grants Related Venues Related Experts View Save	MINGZHU TANG et. al.	ISA transactions	2025-10-31
435	Binary Anomaly Detection in Streaming IoT Traffic Under Concept Drift Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the growing volume of Internet of Things (IoT) network traffic, machinelearning (ML)-based anomaly detection is more relevant than ever. Traditionalbatch learning models face …	Rodrigo Matos Carnier; Laura Lahesoo; Kensuke Fukuda;	arxiv-cs.LG	2025-10-31
436	A Survey of Heterogeneous Graph Neural Networks for Cybersecurity Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To address this gap, we provide a comprehensive surveyof HGNN-based anomaly detection methods in cybersecurity. We introduce ataxonomy that classifies approaches by anomaly type and graph dynamics, analyzerepresentative models, and map them to key cybersecurity applications.	Laura Jiang; Reza Ryan; Qian Li; Nasim Ferdosian;	arxiv-cs.CR	2025-10-30
437	TBM Operational Data-driven Anomaly Detection in Hard Rock Excavations Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Paul J. Unterlass; Mario Wölflingseder; Thomas Marcher;	Tunnelling and Underground Space Technology	2025-10-30
438	MSAD: A Deep Dive Into Model Selection for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Anomaly detection is a fundamental task for time series analytics withimportant implications for the downstream performance of many applications.Despite increasing academic interest and the large number of methods proposedin the literature, recent benchmarks and evaluation studies demonstrated thatno overall best anomaly detection methods exist when applied to veryheterogeneous time series datasets. Therefore, the only scalable and viablesolution to solve anomaly detection over very different time series collectedfrom diverse domains is to propose a model selection method that will select,based on time series characteristics, the best anomaly detection methods torun.	Emmanouil Sylligardos; John Paparrizos; Themis Palpanas; Pierre Senellart; Paul Boniol;	arxiv-cs.LG	2025-10-30
439	Evaluating Large Transformer Models for Anomaly Detection of Resource-constrained IoT Devices for Intrusion Detection System Related Papers Related Patents Related Grants Related Venues Related Experts View Save	AHMAD ALMADHOR et. al.	Scientific Reports	2025-10-30
440	Anomaly Detection in Distribution Power Grids Using Recurrent Neural Networks: A Digital Twin Simulation Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Identifying anomalous behaviors in power grids helps to discover unusual user power consumption, faulty infrastructure, power outages, equipment failures, energy thefts, or …	Barsha Upadhyaya; A. Javaid; Weiqing Sun; Raghav Khanna; William McCreary;	2025 IEEE 16th Annual Information Technology, Electronics …	2025-10-29
441	Deep Learning for Multivariate Time Series Anomaly Detection: An Evaluation of Reconstruction-based Methods IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Abstract In the field of anomaly detection in time series, remarkable advances based on deep learning methodologies and, more specifically, reconstruction-based methods have been proposed.	Mohammed A. Yahya; Antonio R. Moya; Sebastián Ventura;	Artificial Intelligence Review	2025-10-29
442	Knowledge-Guided Textual Reasoning for Explainable Video Anomaly Detection Via LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce Text-based Explainable Video Anomaly Detection (TbVAD), a language-driven framework for weakly supervised video anomaly detection that performs anomaly detection and explanation entirely within the textual domain.	Hari Lee;	arxiv-cs.CV	2025-10-29
443	A Fusion Framework for Anomaly Detection in IoMT Environment Using GraphSAGE and Performer Transformer Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The Internet of Medical Things (IoMT) interconnects medical devices and sensors to enable continuous monitoring and improved patient care. While this connectivity offers …	DIEGO ARTEAGA et. al.	2025 IEEE 16th Annual Information Technology, Electronics …	2025-10-29
444	Subspace-Driven Learning for Anomaly Detection in Process Transients Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Haoyu Yun; Bo Jiang; Jacob Farber; Ahmad Al Rashdan; Hamid Krim;	Nuclear Science and Engineering	2025-10-28
445	Quantitative Benchmarking of Anomaly Detection Methods in Digital Pathology Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection has been widely studied in the context of industrial defect inspection, with numerous methods developed to tackle a range of challenges. In digital pathology, …	CAN CUI et. al.	Machine Learning. Health	2025-10-28
446	Industrial Anomaly Detection Using Mask Attention-based Discriminative Reconstruction Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Renzhen Chen; Lingjun Liu; Jing Tian; Yanting Ai; Fengling Zhang;	Computers and Electrical Engineering	2025-10-28
447	Anomaly Detection of Bearings Under Variable Speeds Using Overcomplete Autoencoder Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Hyeon-Sung Jo; Jung-Woo Sohn;	Transactions of the Korean Society for Noise and Vibration …	2025-10-28
448	FAMRD: Frequency-Aware Multimodal Reverse Distillation for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Second, when one modality indicates normal while another shows anomalies, anomaly detection may be misled by that modality ambiguity. To address these challenges, we propose a Frequency-Aware Multimodal Reverse Distillation (FAMRD) framework from the frequency domain perspective.	QIYIN ZHONG et. al.	mm	2025-10-27
449	BridgeNet: A Unified Multimodal Framework for Bridging 2D and 3D Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Additionally, due to the scarcity of abnormal samples in industrial data, especially in multimodal scenarios, it is necessary to perform anomaly generation to simulate real-world abnormal samples. Therefore, we propose a novel unified multimodal anomaly detection framework to address these issues.	An Xiang; Zixuan Huang; Xitong Gao; Kejiang Ye; Cheng-zhong Xu;	mm	2025-10-27
450	Robust Modality-Incomplete Anomaly Detection: A Modality-Instructive Framework with Benchmark Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To address these, we conduct the first comprehensive study on Modality-Incomplete Industrial Anomaly Detection (MIIAD) and establish MIIAD Bench , a benchmark covering diverse missing settings.	BINGCHEN MIAO et. al.	mm	2025-10-27
451	GRAD: Real-Time Gated Recurrent Anomaly Detection in Autonomous Vehicle Sensors Using Reinforced EMA and Multi-Stage Sliding Window Techniques Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces GRAD, a real-time anomaly detection method forautonomous vehicle sensors that integrates statistical analysis and deeplearning to ensure the reliability of sensor data.	Mohammad Hossein Jafari Naeimi; Ali Norouzi; Athena Abdi;	arxiv-cs.LG	2025-10-27
452	SAGE: A Visual Language Model for Anomaly Detection Via Fact Enhancement and Entropy-aware Alignment Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This limitation stems from the inherently domain-specific nature of anomaly detection, which hinders the applicability of existing VLMs in industrial scenarios that require precise, structured, and context-aware analysis. To address these challenges, we propose SAGE, a VLM-based framework that enhances anomaly reasoning through Self-Guided Fact Enhancement (SFE) and Entropy-aware Direct Preference Optimization (E-DPO).	GUOXIN ZANG et. al.	mm	2025-10-27
453	AnomalyControl: Highly-Aligned Anomalous Image Generation with Controlled Diffusion Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose a controlled anomaly generation model named AnomalyControl to generate realistic anomalous images aligned highly with both text prompts and anomaly masks.	YUANYI DUAN et. al.	mm	2025-10-27
454	Anomaly Detection for Semiconductor Wafer Multi-wire Sawing Machines Using Statistical and Deep Learning Methods Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study, in collaboration with an industry partner, develops two anomaly detection models tailored for diamond multi-wire sawing machines.	Zhen-Yin Annie Chen; Chun-Cheng Lin; Hsin-Cheng Huang; Wen-Chieh Su; Cherng-Yow Cheng;	Mobile Networks and Applications	2025-10-27
455	SP-Mamba: Spatial-Perception State Space Model for Unsupervised Medical Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To capitalize on the inherent structural regularity of medical images, this study introduces SP-Mamba, a spatial-perception Mamba framework for unsupervised medical anomaly detection.	Rui Pan; Ruiying Lu;	mm	2025-10-27
456	Mobile Crowd Sensing for Road Anomaly Detection Using Deep Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Swadesh Jana; Asif Iqbal Middya; Sarbani Roy;	Spatial Information Research	2025-10-27
457	Aggregating Evaluation Metrics for Anomaly Detection: A Unified Scoring Approach Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Alicja Rachwał; Łukasz Gałka; Albert Rachwał; Paweł Karczmarek;	Advances in Science and Technology Research Journal	2025-10-25
458	X-HEART: EXplainable Heterogeneous Log Anomaly Detection Using Robust Transformers Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Paul K. Mvula; Paula Branco; Guy-Vincent Jourdan; Herna L. Viktor;	Knowledge and Information Systems	2025-10-24
459	STaSFormer-SGAD: Semantic Triplet-Aware Spatial Flow-Guided Spatio-Temporal Graph for Anomaly Detection in Surveillance Videos Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Video surveillance is a very common element in various fields such as road surveillance, malls, education, and many other public spots each presenting distinct anomaly patterns …	T. Srikanth; Avinash Reddy Segireddy; S. Elavarasi; S. K; M. K;	2025 International Conference on Communication, Computer, …	2025-10-24
460	A Survey of Research Advances in Federated Learning for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper provides a comprehensive review of the application of FL in various anomaly detection scenarios, including cybersecurity, intelligent industry, and financial services.	Futao Ye;	Science and Technology of Engineering, Chemistry and …	2025-10-23
461	Quantum Autoencoders for Anomaly Detection in Cybersecurity Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Inthis work, we apply Quantum Autoencoders (QAEs) for anomaly detection incybersecurity, specifically on the BPF-extended tracking honeypot (BETH)dataset.	Rohan Senthil; Swee Liang Wong;	arxiv-cs.ET	2025-10-22
462	Multistage Latent Residual Based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Fangdi Xu; Yunxue Shao;	Signal, Image and Video Processing	2025-10-21
463	Anomaly Detection of Integrated Circuits Package Substrates Using The Large Vision Model SAIC: Dataset Construction, Methodology, and Application Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, the progress of IC anomaly detection is hampered by the scarcity of defective samples and the shortage of well-defined annotations. To address this challenge, this paper focuses on the research in the field of IC, especially on ceramic package substrates (CPS).	Ruiyun Yu; Bingyang Guo; Haoyuan Li;	iccv	2025-10-20
464	VelocityNet: Real-Time Crowd Anomaly Detection Via Person-Specific Velocity Analysis Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Detecting anomalies in crowded scenes is challenging due to severeinter-person occlusions and highly dynamic, context-dependent motion patterns.Existing approaches often struggle …	FATIMA ALGHAMDI et. al.	arxiv-cs.CV	2025-10-20
465	ReMP-AD: Retrieval-enhanced Multi-modal Prompt Fusion for Few-Shot Industrial Visual Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Few-shot methods, which use limited samples and prompts, offer a more efficient approach.	Hongchi Ma; Guanglei Yang; Debin Zhao; Yanli Ji; Wangmeng Zuo;	iccv	2025-10-20
466	Kaputt: A Large-Scale Dataset for Visual Defect Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a novel large-scale dataset for defect detection in a logistics setting.	SEBASTIAN H&OUML;FER et. al.	iccv	2025-10-20
467	Bridging 3D Anomaly Localization and Repair Via High-Quality Continuous Geometric Representation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Our code will be released to drive further research.	BOZHONG ZHENG et. al.	iccv	2025-10-20
468	Normal and Abnormal Pathology Knowledge-Augmented Vision-Language Model for Anomaly Detection in Pathology Images Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Existing anomaly detection methods, primarily designed for industrial settings, face limitations in pathology due to computational constraints, diverse tissue structures, and lack of interpretability. To address these challenges, we propose Ano-NAViLa, a Normal and Abnormal pathology knowledge-augmented Vision-Language model for Anomaly detection in pathology images.	JINSOL SONG et. al.	iccv	2025-10-20
469	FE-CLIP: Frequency Enhanced CLIP Model for Zero-Shot Anomaly Detection and Segmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, they overlook the utilization of frequency information of images. In this paper, we find that frequency information could benefit the ZSAD task, since some properties of the anomaly area, such as appearance defects, can also be reflected based on its frequency information.	Tao Gong; Qi Chu; Bin Liu; Wei Zhou; Nenghai Yu;	iccv	2025-10-20
470	SALAD — Semantics-Aware Logical Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose SALAD, a semantics-aware discriminative logical anomaly detection method that incorporates a newly proposed composition branch to explicitly model the distribution of object composition maps, consequently learning important semantic relationships.	Matic Fučka; Vitjan Zavrtanik; Danijel Skočaj;	iccv	2025-10-20
471	Wave-MambaAD: Wavelet-driven State Space Model for Multi-class Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, Mamba-based anomaly detectors still face two critical challenges: (1) insufficient modeling of diverse local features leading to inaccurate detection of subtle anomalies; (2) spatial-wise scanning mechanism disrupting the spatial continuity of large-scale anomalies, resulting in incomplete localization. To address these challenges, we propose Wave-MambaAD, a wavelet-driven state space model for unified subtle and large-scale anomaly detection.	Qiao Zhang; Mingwen Shao; Xinyuan Chen; Xiang Lv; Kai Xu;	iccv	2025-10-20
472	Unsupervised Anomaly Detection Improves Imitation Learning for Autonomous Racing Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Imitation Learning (IL) has shown significant promise in autonomous driving, but its performance heavily depends on the quality of training data. Noisy or corrupted sensor inputs …	YUANG GENG et. al.	2025 IEEE/RSJ International Conference on Intelligent …	2025-10-19
473	Deviation‐Guided Attention for Semi‐Supervised Anomaly Detection With Contrastive Regularisation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: ABSTRACT Anomaly detection (AD) aims to identify abnormal patterns that deviate from normal behaviour, playing a critical role in applications such as industrial inspection, medical imaging and autonomous driving.	GUANGLEI XIE et. al.	CAAI Transactions on Intelligence Technology	2025-10-18
474	Collaborative Real-Time Single-Object Anomaly Detection Framework of Roadside Facilities for Traffic Safety and Management Using Efficient YOLO Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes an Edge AI-based collaborative framework for real-time anomaly detection of roadside facilities to enhance traffic safety and management.	Jiheon Kang; Soohyen Jang; Yoonyoung Choi; Wooyong Lee; Byoungkug Kim;	Applied Sciences	2025-10-17
475	Generating Detectors from Anomaly Samples Via Negative Selection for Network Intrusion Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Negative selection algorithms (NSAs), which simulate the human immune mechanism for network anomaly detection, represent a promising approach in this field.	Zhiyong Li; Xiang Wei; Chunyan Li; Jianhong Sun;	Scientific reports	2025-10-17
476	SMART VISION SYSTEMS FOR PUBLIC SAFETY: REAL-TIME CROWD MONITORING AND ANOMALY DETECTION IN URBAN SPACES USING DEEP LEARNING AND EDGE COMPUTING Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents ConvLSTM, an online deep learning model, which is targeted for intelligent crime surveillance and anomaly detection in densely populated urban areas.	J. Anvar Shathik;	International Journal of Applied Mathematics	2025-10-15
477	Anomaly Detection in Urban Lighting Systems Using Autoencoder and Transformer Algorithms Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The study aims to present the effectiveness of anomaly detection algorithms in lighting systems based on analyzing records from electricity meters.	Tomasz Śmiałkowski; Andrzej Czyżewski;	Scientific reports	2025-10-15
478	Scalable and Real-Time Temporal Anomaly Detection in Enterprise Log Data: A Hierarchical Transformer-based Framework Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The anomaly detection in enterprise log data plays an important role in recognizing threats, misconfigurations, and failures of operations. Hierarchical nature and temporal …	B. A; Arigala Reddyroshan; A. Amulya; Chekka Karthikeya; Ambiti Girish;	2025 International Conference on Sustainable Communication …	2025-10-15
479	Text Anomaly Detection with Simplified Isolation Kernel Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To address thischallenge, we introduce the Simplified Isolation Kernel (SIK), which mapshigh-dimensional dense embeddings to lower-dimensional sparse representationswhile preserving crucial anomaly characteristics.	Yang Cao; Sikun Yang; Yujiu Yang; Lianyong Qi; Ming Liu;	arxiv-cs.CL	2025-10-15
480	Isolation-based Spherical Ensemble Representations for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce a novel similarity-based scoring method that measurespattern consistency by comparing ensemble representations against a theoreticalanomaly reference pattern.	YANG CAO et. al.	arxiv-cs.LG	2025-10-15
481	Generative Modeling for Interpretable Anomaly Detection in Medical Imaging: Applications in Failure Detection and Data Curation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: This work aims to leverage generative modeling-based anomaly detection to enhance interpretability in AI failure detection systems and to aid data curation for large repositories. …	MCKELL E WOODLAND et. al.	Bioengineering (Basel, Switzerland)	2025-10-14
482	A Comprehensive Forecasting-Based Framework for Time Series Anomaly Detection: Benchmarking on The Numenta Anomaly Benchmark (NAB) Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present acomprehensive forecasting-based framework unifying classical methods(Holt-Winters, SARIMA) with deep learning architectures (LSTM, Informer) undera common residual-based detection interface.	Mohammad Karami; Mostafa Jalali; Fatemeh Ghassemi;	arxiv-cs.LG	2025-10-13
483	Performance Measurement of Bayesian Online Changepoint Detection and Its Application Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Recently with the proliferation of open data, time series analysis has garnered significant attention. In particular, analyses exploiting complex anomalies identifiable through …	Masaki Shimono; Kaiyu Suzuki; Masahiro Kobayashi; Shigeo Akashi; Tomofumi Matsuzawa;	International Conference on Advanced Robotics, Automation …	2025-10-13
484	Towards Realistic Industrial Anomaly Detection: MADE-Net Framework and ManuDefect-21 Benchmark Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The proposed framework and dataset jointly contribute to advancing practical and reproducible research in industrial anomaly detection.	Junyang Yang; Jiuxin Cao; Chengge Duan;	Applied Sciences	2025-10-10
485	ASBench: Image Anomalies Synthesis Benchmark for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Current research also overlook crucial factors specificto anomaly synthesis, such as decoupling its impact from detection,quantitative analysis of synthetic data and adaptability across differentscenarios. To address these limitations, we propose ASBench, the firstcomprehensive benchmarking framework dedicated to evaluating anomaly synthesismethods.	QUNYI ZHANG et. al.	arxiv-cs.CV	2025-10-09
486	Evaluating Anomaly Detection Algorithms: The Role of Hyperparameters and Standardized Benchmarks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection is a cornerstone of machine learning with applications spanning healthcare, fraud detection, and scientific discovery. Despite extensive research, fair …	Simon Klüttermann; Shubham Gupta; Emmanuel Müller;	2025 IEEE 12th International Conference on Data Science and …	2025-10-09
487	Meta-Learning Based Few-Shot Graph-Level Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Additionally, few-shot anomaly detection methods based onGNNs are prone to noise interference, resulting in poor embedding quality andreduced model robustness. To address these challenges, we propose a novelmeta-learning-based graph-level anomaly detection framework (MA-GAD),incorporating a graph compression module that reduces the graph size,mitigating noise interference while retaining essential node information.	Liting Li; Yumeng Wang; Yueheng Sun;	arxiv-cs.LG	2025-10-09
488	LLM-Driven Adaptive Prompt Optimization Framework for ADS-B Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Existing ADS-B anomaly detection methods still suffer from significant limitations, including low anomaly detection rates and limited adaptability. To address these issues, this paper proposes a novel ADS-B anomaly detection framework driven by large language models (LLMs).	Siqi Li; Buhong Wang; Zhengyang Zhao; Yong Yang; Yongjian Guan;	Aerospace	2025-10-09
489	Vacuum Spiker: A Spiking Neural Network-Based Model for Efficient Anomaly Detection in Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Experimental results on publicly availabledatasets show that the proposed algorithm achieves competitive performancewhile significantly reducing energy consumption, compared to a wide set of deeplearning and machine learning baselines.	Iago Xabier Vázquez; Javier Sedano; Muhammad Afzal; Ángel Miguel García-Vico;	arxiv-cs.LG	2025-10-08
490	Drone-Based Anomaly and Person Detection System Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a study on integrating artificial intelligence techniques, including computer vision and deep learning, to design an autonomous drone system for enhanced situational awareness.	Dr.K. Malarvizhi; M. Kohila; S. Sherlin; M.Arivu Selvan; K.Praveen Kumar;	INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING …	2025-10-08
491	Kaputt: A Large-Scale Dataset for Visual Defect Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a novel large-scale dataset for defect detection in a logisticssetting.	SEBASTIAN HÖFER et. al.	arxiv-cs.CV	2025-10-07
492	Ensemble Pruning-based Anomaly Detection for Improving Data Quality in Ladle Furnace Temperature Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes an ensemble pruning-based anomaly-detection method.	Yanli Song; Qing Wang; Biao Wang;	Transactions of the Institute of Measurement and Control	2025-10-07
493	A Context-Adaptive Hyperspectral Sensor and Perception Management Architecture for Airborne Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: These requirements have rarely been met in current research, as evaluations are still predominantly based on small, context-restricted datasets, offering only limited insights into detector performance under varying conditions. To address this gap, we propose a context-adaptive hyperspectral sensor and perception management (hSPM) architecture that integrates sensor context extraction, band selection, and detector management into a single adaptive processing pipeline.	Linda Eckel; Peter Stütz;	Sensors (Basel, Switzerland)	2025-10-06
494	Non-Contact Acoustic Slide Anomaly Detection Method Based on Spectrum Compression Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To solve the issues, a new slide quality detection method was proposed.	Yanping Fan; kun yang; Hongli Qi; Tao Li; dawei zhang;	Engineering Research Express	2025-10-06
495	Dual-level Anomaly Synthesis Network for Weak Anomaly Detection in Liquid Crystal Displays Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Sijie Luo; Huaixin Chen; Biyuan Liu; Ruoyu Yang; Zhixi Wang;	Displays	2025-10-06
496	Anomaly-Aware YOLO: A Frugal Yet Robust Approach to Infrared Small Target Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Infrared Small Target Detection (IRSTD) is a challenging task in defenseapplications, where complex backgrounds and tiny target sizes often result innumerous false alarms using conventional object detectors. To overcome thislimitation, we propose Anomaly-Aware YOLO (AA-YOLO), which integrates astatistical anomaly detection test into its detection head.	Alina Ciocarlan; Sylvie Le Hégarat-Mascle; Sidonie Lefebvre;	arxiv-cs.CV	2025-10-06
497	HADDNLP: Hyperspectral Anomaly Detection Via Double Nonlocal Priors Related Papers Related Patents Related Grants Related Venues Related Experts View Save	LONGFEI REN et. al.	Pattern Recognition	2025-10-05
498	SymmFlow: Unsupervised Anomaly Detection Via Symmetric Normalizing Flow Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Zeyu Zhang; Danqing Kang; Biaohua Ye; Jianhuang Lai;	Computers in Industry	2025-10-04
499	THEMIS: Unlocking Pretrained Knowledge with Foundation Model Embeddings for Anomaly Detection in Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: THEMIS extractsembeddings from the encoder of the Chronos time series foundation model andapplies outlier detection techniques like Local Outlier Factor and SpectralDecomposition on the self-similarity matrix, to spot anomalies in the data. Ourexperiments show that this modular method achieves SOTA results on the MSLdataset and performs quite competitively on the SMAP and SWAT$^*$ datasets.Notably, THEMIS exceeds models trained specifically for anomaly detection,presenting hyperparameter robustness and interpretability by default.	Yadav Mahesh Lorik; Kaushik Sarveswaran; Nagaraj Sundaramahalingam; Aravindakumar Venugopalan;	arxiv-cs.LG	2025-10-04
500	Incorporating Civilian Radioxenon Background Estimates in Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	RAMESH S. SARATHI et. al.	Journal of Environmental Radioactivity	2025-10-04
501	SPEAR: Soft Prompt Enhanced Anomaly Recognition for Time Series Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Time series anomaly detection plays a crucial role in a wide range of fields,such as healthcare and internet traffic monitoring. The emergence of largelanguage models (LLMs) …	Hanzhe Wei; Jiajun Wu; Jialin Yang; Henry Leung; Steve Drew;	arxiv-cs.LG	2025-10-04
502	VARNet-6G with FIERO Model for Anomaly Detection and Enhancing Network Stability in Future-ready Communication Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Most of the anomaly detection models until now are encumbered with the issues of scalability, being adaptable to new types of attacks, and the capability of processing large, dynamic network data efficiently. In order to address these challenges, this paper proposes two new techniques: the Variational Autoencoder and Recurrent Transformer Network for 6G (VARNet-6G) for anomaly detection and the Flamingo-Infused Evaporation Rate Optimizer (FIERO) for dropout rate estimation.	S Sankar Ganesh; Maha Abdelhaq; SatheeshKumar Palanisamy; S Janakiraman;	Scientific reports	2025-10-02
503	Detecting Imbalanced Credit Card Fraud Via Hybrid Graph Attention and Variational Autoencoder Ensembles Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Credit card fraud detection remains a major challenge due to severe class imbalance and the constantly evolving nature of fraudulent behaviors. To address these challenges, this …	Ibomoiye Domor Mienye; Ebenezer Esenogho; Cameron Modisane;	AppliedMath	2025-10-02
504	Moon: A Modality Conversion-based Efficient Multivariate Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, these methods face twokey challenges: (1) Unsupervised learning methods, such as reconstruction-basedand prediction-based methods, rely on error thresholds, which can lead toinaccuracies; (2) Semi-supervised methods mainly model normal data and oftenunderuse anomaly labels, limiting detection of subtle anomalies;(3) Supervisedlearning methods, such as classifier-based approaches, often fail to capturelocal relationships, incur high computational costs, and are constrained by thescarcity of labeled data. To address these limitations, we propose Moon, asupervised modality conversion-based multivariate time series anomaly detectionframework.	YUANYUAN YAO et. al.	arxiv-cs.LG	2025-10-02
505	Frequency-Domain Anomaly Detection for Encrypted Traffic in Industrial Control Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Industrial control systems (ICSs) are becoming increasingly interconnected, rendering them susceptible to cyber attacks. Timely detection of anomalies in encrypted data flows is …	Zhangfa Wu; Huifang Li; Yi Hua; Nguyen H. Tran; Hongping Gan;	IEEE Transactions on Industrial Informatics	2025-10-01
506	TraceDAE: Trace-Based Anomaly Detection in Microservice Systems Via Dual Autoencoder Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Microservice systems have become a popular architecture for modern Web applications owing to their scalability, modularity, and maintainability. However, with the increasing …	Junjun Li; Shi Ying; Tiangang Li; Xiangbo Tian;	IEEE Transactions on Network and Service Management	2025-10-01
507	Improved PCA Reconstruction-Based Unsupervised Anomaly Detection in Uncontrolled Structural Health Monitoring With Correntropy Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Guided wave-based structural health monitoring is extensively utilized in various industrial applications to ensure the integrity of components within industrial systems. Among …	KANG YANG et. al.	IEEE Transactions on Industrial Informatics	2025-10-01
508	MIRDETECTOR: Applying Malicious Intent Representation for Enhanced APT Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	HONGMEI LI et. al.	Comput. Secur.	2025-10-01
509	A Spacecraft Anomaly Detection Method Based on Multi-Component Self-Attention and Association Discrepancy Evaluation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Spacecraft anomaly detection has become a crucial task in aerospace engineering. Since the anomalies are quite rare in telemetry data, unsupervised learning has been applied to …	Jingyi Chen; Cai Lanbo; Yongqing Wang; Zhifeng Ma;	Journal of Physics: Conference Series	2025-10-01
510	Time Series Anomaly Detection Based on Enhanced Anomaly Simulation and Triplet Contrastive Knowledge Base Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yu Xia; Zhizhong Mao;	Knowl. Based Syst.	2025-10-01
511	Anomaly Detection Using Graph Anomaly Rules Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Bowen Dong; Wenjun Wang; Lifei Sun; Xueli Liu; Zhenzhen Mai;	Big Data Min. Anal.	2025-10-01
512	Hyperspectral Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Mrs.G. Hemaprabha; A. M. Arafath; P. M. Sidhik; S. NandhaKishore; M. Nikitha;	International Journal of Research Publication and Reviews	2025-10-01
513	Dynamic Expert Routing for Unsupervised Continual Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Unsupervised continual anomaly detection (UCAD) aims to develop a model that can continuously learn in dynamic scenarios while avoiding forgetting previously acquired knowledge …	Yuxuan Cai; Xinwei He; Ao Tong; X. Bai;	IEEE Transactions on Industrial Informatics	2025-10-01
514	BGP Anomaly Detection Using The Raw Internet Topology Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Hamid Latif-Martínez; Jordi Paillissé; P. Barlet-Ros; Alberto Cabellos-Aparicio;	Comput. Networks	2025-10-01
515	Robust Spatiotemporally Contiguous Anomaly Detection Using Tensor Decomposition Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce an unsupervisedtensor-based anomaly detection method that simultaneously considers the sparseand spatiotemporally smooth nature of anomalies.	Rachita Mondal; Mert Indibi; Tapabrata Maiti; Selin Aviyente;	arxiv-cs.LG	2025-09-30
516	TSAD: Transformer-Based Semi-Supervised Anomaly Detection for Dynamic Graphs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection aims to identify abnormal instances that significantly deviate from normal samples. With the natural connectivity between instances in the real world, graph …	Jin Zhang; Ke Feng;	Mathematics	2025-09-30
517	A Swin Transformer-based Hybrid Reconstruction Discriminative Network for Image Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Industrial anomaly detection algorithms based on Convolutional Neural Networks (CNN) often struggle with identifying small anomaly regions and maintaining robust performance in noisy industrial environments. To address these limitations, this paper proposes the Swin Transformer-Based Hybrid Reconstruction Discriminative Network (SRDAD), which combines the global context modeling capabilities of Swin Transformer with complementary reconstruction and discrimination approaches.	JIN JIN et. al.	Scientific reports	2025-09-30
518	PatchEAD: Unifying Industrial Visual Prompting Frameworks for Patch-Exclusive Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We aim to address thislimitation by proposing a unified patch-focused framework, Patch-ExclusiveAnomaly Detection (PatchEAD), enabling training-free anomaly detection that iscompatible with diverse foundation models.	Po-Han Huang; Jeng-Lin Li; Po-Hsuan Huang; Ming-Ching Chang; Wei-Chao Chen;	arxiv-cs.CV	2025-09-30
519	Generalist Multi-Class Anomaly Detection Via Distillation to Two Heterogeneous Student Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Although recent methods have attempted toaddress general anomaly detection, their performance remains sensitive todataset-specific settings and single-class tasks. In this paper, we propose anovel dual-model ensemble approach based on knowledge distillation (KD) tobridge this gap.	Hangil Park; Yongmin Seo; Tae-Kyun Kim;	arxiv-cs.CV	2025-09-29
520	Research on Online Log Anomaly Detection Model Based on Informer Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: To address the limitations of conventional reactive log anomaly detection in high‐availability systems, this paper presents OADS—an online anomaly detection system that synergizes …	Yimin Guo; Yilin Sun; Ping Xiong;	Concurrency and Computation: Practice and Experience	2025-09-28
521	Anomaly Detection By Clustering DINO Embeddings Using A Dirichlet Process Mixture Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we leverage informative embeddings from foundational models forunsupervised anomaly detection in medical imaging.	Nico Schulthess; Ender Konukoglu;	arxiv-cs.CV	2025-09-24
522	Exploring The Potential of Anomaly Detection Through Reasoning with Large Language Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In recent years, anomaly detection in digital environments has become a critical research area due to issues such as spam messages and fake news, which can lead to privacy …	Sungjune Park; Daeseon Choi;	Applied Sciences	2025-09-24
523	An Improved Time Series Anomaly Detection By Applying Structural Similarity Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, accurate anomaly detectionremains an unsettled challenge, since the optimization objectives ofreconstruction-based methods merely rely on point-by-point distance measures,ignoring the potential structural characteristics of time series and thusfailing to tackle complex pattern-wise anomalies. In this paper, we proposeStrAD, a novel structure-enhanced anomaly detection approach to enrich theoptimization objective by incorporating structural information hidden in thetime series and steering the data reconstruction procedure to better capturesuch structural features.	TIEJUN WANG et. al.	arxiv-cs.LG	2025-09-24
524	Periodic Graph-Enhanced Multivariate Time Series Anomaly Detector Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Multivariate time series (MTS) anomaly detection commonly encounters invarious domains like finance, healthcare, and industrial monitoring. However,existing MTS anomaly detection …	Jia Li; Shiyu Long; Ye Yuan;	arxiv-cs.LG	2025-09-22
525	Robust Anomaly Detection Under Normality Distribution Shift in Dynamic Graphs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Anomaly detection in dynamic graphs is a critical task with broad real-worldapplications, including social networks, e-commerce, and cybersecurity. Mostexisting methods assume that normal patterns remain stable over time; however,this assumption often fails in practice due to the phenomenon we refer to asnormality distribution shift (NDS), where normal behaviors evolve over time.Ignoring NDS can lead models to misclassify shifted normal instances asanomalies, degrading detection performance.	Xiaoyang Xu; Xiaofeng Lin; Koh Takeuchi; Kyohei Atarashi; Hisashi Kashima;	arxiv-cs.LG	2025-09-22
526	From Benchmarks to Reality: Advancing Visual Anomaly Detection By The VAND 3.0 Challenge Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Visual anomaly detection is a strongly application-driven field of research.Consequently, the connection between academia and industry is of paramountimportance. In this regard, we present the VAND 3.0 Challenge to showcasecurrent progress in anomaly detection across different practical settingswhilst addressing critical issues in the field.	LARS HECKLER-KRAM et. al.	arxiv-cs.CV	2025-09-22
527	Anomaly Detection By Partitioning of Multi-variate Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this article, we suggest a novel non-supervised partition based anomalydetection method for anomaly detection in multivariate time series calledPARADISE.	Pierre Lotte; André Péninou; Olivier Teste;	arxiv-cs.LG	2025-09-22
528	Graph Enhanced Trajectory Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To improve the robustness of anomaly detection, we introduce ConfidenceWeighted Negative Log Likelihood (CW NLL), an anomaly scoring function thatemphasizes high-confidence deviations.	Jonathan Kabala Mbuya; Dieter Pfoser; Antonios Anastasopoulos;	arxiv-cs.LG	2025-09-22
529	Research on Proactive Network Security Detection Algorithm Based on Machine Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In this paper, we introduce anomaly detection on the basis of misuse detection, and propose an active network security detection algorithm based on machine learning. Firstly, the …	Bin Luo;	International Conference on Machine Vision, Automatic …	2025-09-19
530	Ort Anomaly Detection and Risk Factor Extraction Integrated with AI Algorithms Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: A report is a presentation medium for various types of data, and its anomaly identification and risk factor extraction have great value in ensuring the transparency of information …	Wenna Guo; Yong Yang;	International Conference on Mechatronics and Artificial …	2025-09-19
531	A Novel Anomaly Detection Method for Magnetic Flux Leakage Signals Via A Feature-based Unsupervised Detection Network Related Papers Related Patents Related Grants Related Venues Related Experts View Save	He Zhao; Jinhai Liu; Qiannan Wang; Xiangkai Shen; Lin Jiang;	Computers in Industry
532	AD-DINOv3: Enhancing DINOv3 for Zero-Shot Anomaly Detection with Anomaly-Aware Calibration Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, weare the first to adapt DINOv3 for ZSAD.	Jingyi Yuan; Jianxiong Ye; Wenkang Chen; Chenqiang Gao;	arxiv-cs.CV	2025-09-17
533	Anomaly Detection of CAN Bus Messages on Neuromorphic Hardware Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection is becoming an essential component of the modern automotive industry. With the increasing prevalence of smart vehicles, the number of Electronic Control Units …	RASHEDUL ISLAM et. al.	Optical Engineering + Applications	2025-09-16
534	Adaptive-GraphSketch: Real-Time Edge Anomaly Detection Via Multi-Layer Tensor Sketching and Temporal Decay Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose ADAPTIVE-GRAPHSKETCH, a lightweightand scalable framework for real-time anomaly detection in streaming edge data.Our method integrates temporal multi-tensor sketching with Count-Min Sketchusing Conservative Update (CMS-CU) to compactly track edge frequency patternswith bounded memory, while mitigating hash collision issues.	Ocheme Anthony Ekle; William Eberle;	arxiv-cs.LG	2025-09-15
535	Measurement-driven LSAD: An Interpretable Lightweight Distillation Framework for Edge-device Industrial Logical Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In industrial anomaly detection, large-scale models are widely used for texture analysis and defect recognition. However, lightweight deployment still faces challenges in …	Shenglei Pei; Jinchang Cheng; Shoupeng Zhang; Boxiao Luo;	Measurement Science and Technology	2025-09-15
536	Two-Stage Framework For Enhanced Hyperspectral Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	CHI ZHANG et. al.	2025 IEEE International Conference on Image Processing …	2025-09-14
537	Synthetic Data Generation with Lorenzetti for Time Series Anomaly Detection in High-Energy Physics Calorimeters Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection in multivariate time series is crucial to ensure thequality of data coming from a physics experiment. Accurately identifying themoments when unexpected errors or …	Laura Boggia; Bogdan Malaescu;	arxiv-hep-ex	2025-09-09
538	A Review on Anomaly Detection for Connected Vehicles Using Deep Reinforcement Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The transition to connected vehicles (CVs) is shaping the future of autonomous and highly connected vehicles. As the vehicles’ reliance on increasingly complex software increases, …	MATTHIAS WEISS et. al.	2025 IEEE 30th International Conference on Emerging …	2025-09-09
539	Optimizing PatchCore for One-Shot Industrial Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: PatchCore is a widely used algorithm for industrial anomaly detection, due to its high performance compared to alternative approaches. This paper focuses on optimizing its …	Simona Zlatanova; Piercarlo Dondi; Marco Porta; Michele Antolini;	2025 IEEE 30th International Conference on Emerging …	2025-09-09
540	GenAI-Based Digital Twins Aided Data Augmentation Increases Accuracy in Real-Time Cokurtosis-Based Anomaly Detection of Wearable Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Through our work, we present an enhanced method for early anomaly detection in multivariate datasets, with promising applications in healthcare and beyond.	METHUN KAMRUZZAMAN et. al.	Sensors (Basel, Switzerland)	2025-09-07
541	A Dual-Discriminator Generative Adversarial Network for Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Multivariate time series anomaly detection has shown potential in various fields, such as finance, aerospace, and security. The fuzzy definition of data anomalies, the complexity …	Da Ding; Youquan Wang; Haicheng Tao; Jia Wu; Jie Cao;	IEEE transactions on neural networks and learning systems	2025-09-05
542	Towards Efficient Pixel Labeling for Industrial Anomaly Detection and Localization Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Industrial product inspection is often performed using Anomaly Detection (AD)frameworks trained solely on non-defective samples.	JINGQI WU et. al.	arxiv-cs.CV	2025-09-05
543	Detectability Driven Recommendation of Anomaly Detection Models for Time-Series Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection for time-series data has been viewed widely in many practical applications and caused lots of research interests. A popular solution based on deep learning …	XIANMIN LIU et. al.	IEEE transactions on cybernetics	2025-09-04
544	Revolutionising Anomaly Detection: A Hybrid Framework for Anomaly Detection Integrating Isolation Forest, Autoencoder, and Conv. LSTM Related Papers Related Patents Related Grants Related Venues Related Experts View Save	ANKIT KUMAR et. al.	Knowledge and Information Systems	2025-09-04
545	Conditional Deep Generative Normative Modeling for Structural and Developmental Anomaly Detection in The Fetal Brain Related Papers Related Patents Related Grants Related Venues Related Experts View Save	SUNGMIN YOU et. al.	NeuroImage	2025-09-03
546	SALAD – Semantics-Aware Logical Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Recent surface anomaly detection methods excel at identifying structural anomalies, such as dents and scratches, but struggle with logical anomalies, such as irregular or missing …	Matic Fucka; Vitjan Zavrtanik; D. Skočaj;	ArXiv	2025-09-02
547	Physics-informed Tensor Autoencoder with Memory for Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Jianan Liu; Chunguang Li;	Expert Syst. Appl.	2025-09-01
548	FAD: Feature Augmented Distillation for Anomaly Detection and Localization Related Papers Related Patents Related Grants Related Venues Related Experts View Save	QIYIN ZHONG et. al.	Expert Syst. Appl.	2025-09-01
549	DEWMA-IForest: Abnormal Detection Method for Subcomponents of Aircraft Air Conditioning System Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The characteristics of aircraft air conditioning systems are complex operating conditions and high coupling of components, which make it difficult for traditional aircraft …	Yanfei Han; Zixuan Bai; Tong Mu; Lunlong Zhong; Renbiao Wu;	Journal of Physics: Conference Series	2025-09-01
550	CA-VAD: Caption Aware Video Anomaly Detection in Surveillance Videos Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Debi Prasad Senapati; S. Pani; Santos Kumar Baliarsingh; Prabhu Prasad Dev; Hrudaya Kumar Tripathy;	J. Vis. Commun. Image Represent.	2025-09-01
551	Deep Learning for Anomaly Detection in Environmental Monitoring Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection in environmental datasets is critical for identifying unusual patterns that could signal potential hazards or changes in environmental conditions. Traditional …	A. PRASAD et. al.	2025 IEEE International Conference on Advanced Computing …	2025-09-01
552	A Self-adaptive Hybrid Network Anomaly Detection Engine Related Papers Related Patents Related Grants Related Venues Related Experts View Save	A. Bagha; I. Woungang; I. Traoré; Danda B. Rawat;	Comput. Commun.	2025-09-01
553	Progressive Self-supervised Framework for Anomaly Detection in Hyperspectral Images Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Pan Liu; Yuanyang Bu; Yongqiang Zhao; Seong G. Kong;	Eng. Appl. Artif. Intell.	2025-09-01
554	Enhancing Surveillance Anomaly Detection with Keyframes and Explainable Inception Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save	MUHAMMAD SALMAN et. al.	Egyptian Informatics Journal	2025-09-01
555	Early Fatigue Failure Detection in Composites Using Autoencoder-Based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Ali Ebrahimi; Farjad Shamehri; Suong van Hoa;	Composites Part B: Engineering	2025-09-01
556	RTdetector: Deep Transformer Networks for Time Series Anomaly Detection Based on Reconstruction Trend Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection in multivariate time series data is critical across a variety of real-life applications. The predominant anomaly detection techniques currently rely on …	Xinhong Liu; Xiaoliang Li; Yangfan Li; Fengxiao Tang; Ming Zhao;	International Joint Conference on Artificial Intelligence	2025-09-01
557	Quantum Enhanced Ensemble GANs for Anomaly Detection in Continuous Biomanufacturing Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we present a novel framework forunsupervised anomaly detection in continuous biomanufacturing based on anensemble of generative adversarial networks (GANs).	RAJIV KAILASANATHAN et. al.	arxiv-cs.LG	2025-08-29
558	TMUAD: Enhancing Logical Capabilities in Unified Anomaly Detection Models with A Text Memory Bank Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Specifically, we propose a Three-Memory framework for Unifiedstructural and logical Anomaly Detection (TMUAD).	JIAWEI LIU et. al.	arxiv-cs.CV	2025-08-29
559	CALM: A Framework for Continuous, Adaptive, and LLM-Mediated Anomaly Detection in Time-Series Streams Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Traditional models, trained offline, suffer significant performancedegradation when faced with concept drift, where the underlying statisticalproperties of the data change over time. This paper introduces CALM(Continuous, Adaptive, and LLM-Mediated), a novel, end-to-end framework forreal-time anomaly detection designed to address this challenge.	Ashok Devireddy; Shunping Huang;	arxiv-cs.LG	2025-08-28
560	Context-Aware Zero-Shot Anomaly Detection in Surveillance Using Contrastive and Predictive Spatiotemporal Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work introduces a novelcontext-aware zero-shot anomaly detection framework that identifies abnormalevents without exposure to anomaly examples during training.	Md. Rashid Shahriar Khan; Md. Abrar Hasan; Mohammod Tareq Aziz Justice;	arxiv-cs.CV	2025-08-25
561	DRTA: Dynamic Reward Scaling for Reinforcement Learning in Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To overcome thesechallenges, we propose a reinforcement learning-based framework that integratesdynamic reward shaping, Variational Autoencoder (VAE), and active learning,called DRTA.	Bahareh Golchin; Banafsheh Rekabdar; Kunpeng Liu;	arxiv-cs.LG	2025-08-25
562	Fence Off Anomaly Interference: Cross-Domain Distillation for Fully Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, due to thepresence of anomalies in the training data, traditional KD methods riskenabling the student to learn the teacher’s representation of anomalies underFUAD setting, thereby resulting in poor anomaly detection performance. Toaddress this issue, we propose a novel Cross-Domain Distillation (CDD)framework based on the widely studied reverse distillation (RD) paradigm.Specifically, we design a Domain-Specific Training, which divides the trainingset into multiple domains with lower anomaly ratios and train a domain-specificstudent for each.	Xinyue Liu; Jianyuan Wang; Biao Leng; Shuo Zhang;	arxiv-cs.CV	2025-08-25
563	ARTPS: Depth-Enhanced Hybrid Anomaly Detection and Learnable Curiosity Score for Autonomous Rover Target Prioritization Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present ARTPS (Autonomous Rover Target Prioritization System), a novelhybrid AI system that combines depth estimation, anomaly detection, andlearnable curiosity scoring for autonomous exploration of planetary surfaces.Our approach integrates monocular depth estimation using Vision Transformerswith multi-component anomaly detection and a weighted curiosity score thatbalances known value, anomaly signals, depth variance, and surface roughness.The system achieves state-of-the-art performance with AUROC of 0.94, AUPRC of0.89, and F1-Score of 0.87 on Mars rover datasets.	Poyraz Baydemir;	arxiv-cs.CV	2025-08-23
564	Generative Adversarial Learning for Anomaly Detection in High-Volume Data Streams Over Fog Computing Layers IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The problem of anomaly detection in high volume data stream has become significantly challenging in fog computing environments where real time processing and resource constraint …	SUCHITH CHANDRAPPA et. al.	2025 2nd International Conference on Intelligent Algorithms …	2025-08-22
565	Beyond Human-prompting: Adaptive Prompt Tuning with Semantic Alignment for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Our system not only advances pixel-wise anomaly detection,but also achieves state-of-the-art performance on multiple benchmark datasetswithout requiring prior knowledge for prompt crafting, establishing a robustand versatile solution for real-world anomaly detection.	PI-WEI CHEN et. al.	arxiv-cs.CV	2025-08-22
566	Pathology-Informed Latent Diffusion Model for Anomaly Detection in Lymph Node Metastasis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Anomaly detection is an emerging approach in digital pathology for itsability to efficiently and effectively utilize data for disease diagnosis.While supervised learning approaches deliver high accuracy, they rely onextensively annotated datasets, suffering from data scarcity in digitalpathology.	JIAMU WANG et. al.	arxiv-eess.IV	2025-08-21
567	Introducing Fast Fourier Convolutions Into Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose FFC-AD, a reconstruction framework using Fourier Feature Convolutions (FFCs) to capture global information early, and we introduce Hidden Space Anomaly Simulation (HSAS), a latent-space regularization strategy that mitigates overgeneralization.	Zhen Zhao; Jiali Zhou;	Sensors (Basel, Switzerland)	2025-08-21
568	CGTS: Graph Transformer-based Anomaly Detection in Controller Area Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save	XUE ZHOU et. al.	Cybersecurity	2025-08-21
569	Anomaly Detection Model Based on Anomaly Representation Reinforcement and Path Iterative Modeling Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In complex systems, mutual influence among sensors can lead to gradual accumulation and spread of anomalies, eventually triggering systemic failures. During this process, abnormal …	Xiangling Chen; Weifu Zhu; Zhixia Zeng; Zhipeng Qiu; Ruliang Xiao;	Concurrency and Computation: Practice and Experience	2025-08-21
570	Adaptive Anomaly Detection in Evolving Network Environments Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce NetSight, aframework for supervised anomaly detection in network data that continuallydetects and adapts to distribution shifts in an online manner.	Ehssan Mousavipour; Andrey Dimanchev; Majid Ghaderi;	arxiv-cs.CR	2025-08-20
571	Advanced Network Traffic Analysis for Intrusion Detection Using RNN and CNN Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: As digital infrastructures expand, so do the complexities of cyber threats, making anomaly detection critical for network security. This research investigates the performance of …	Hassan Rehan;	2025 9th International Conference on Man-Machine Systems …	2025-08-18
572	Towards High-Resolution Industrial Image Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Despite some progress, recent studieshave attempted to improve detection resolution by employing lightweightnetworks or using simple image tiling and ensemble methods.	Ximiao Zhang; Min Xu; Xiuzhuang Zhou;	arxiv-cs.CV	2025-08-18
573	Robust Anomaly Detection of Rotating Machinery with Contaminated Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Rotating machinery is critical to industrial systems, necessitating robust anomaly detection (AD) to ensure operational safety and prevent failures. However, in real-world …	Jingcheng Wen; Jiaxin Ren; Zhibin Zhao; Xuefeng Chen;	Journal of Dynamics, Monitoring and Diagnostics	2025-08-18
574	Federated Learning for Anomaly Detection: A Systematic Review on Scalability, Adaptability, and Benchmarking Framework Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection plays an increasingly important role in maintaining the stability and reliability of modern distributed systems. Federated Learning (FL) is an emerging method …	Le-Hang Lim; Lee-Yeng Ong; M. Leow;	Future Internet	2025-08-18
575	ABNet: Mitigating Sample Imbalance in Anomaly Detection Within Dynamic Graphs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Moreover, GNN-based approaches often prioritize normal samples, neglecting rare anomalies. To address these issues, we propose the Anomaly Balance Network (ABNet), designed to alleviate sample imbalance and enhance anomaly detection.	Yifan Hong; Muhammad Asif Ali; Huan Wang; Junyang Chen; Di Wang;	ijcai	2025-08-16
576	Template3D-AD: Point Cloud Template Matching Method Based on Center Points for 3D Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Considering that the appearance of anomalies is related to the change of surface shape, this paper proposes a curvature-based local feature representation method, which increases the feature difference between abnormal surfaces and normal surfaces.	Yi Liu; Changsheng Zhang; Yufei Yang;	ijcai	2025-08-16
577	MEGAD: A Memory-Efficient Framework for Large-Scale Attributed Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose a Memory-Efficient framework for large-scale attributed Graph Anomaly Detection (MEGAD).	YIFAN ZHANG et. al.	ijcai	2025-08-16
578	AI-Driven Anomaly Detection in Distributed Systems: A Scalable and Sustainable Monitoring Framework Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Distributed systems play an important role in processing large-scale real-time data. However, with a large number of computing nodes joining in, the volume of data becomes very …	Lei Luan; Ling Long; Burra Venkata Durga Kumar;	2025 IEEE 8th International Conference on Computer and …	2025-08-15
579	Physics-Informed Diffusion Models for Unsupervised Anomaly Detection in Multivariate Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose an unsupervised anomaly detection approach based on aphysics-informed diffusion model for multivariate time series data.	Juhi Soni; Markus Lange-Hegermann; Stefan Windmann;	arxiv-cs.LG	2025-08-15
580	Federated Anomaly Detection for Multi-Tenant Cloud Platforms with Personalized Modeling Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes an anomaly detection method based on federated learningto address key challenges in multi-tenant cloud environments, including dataprivacy leakage, heterogeneous resource behavior, and the limitations ofcentralized modeling.	Yuxi Wang; Heyao Liu; Nyutian Long; Guanzi Yao;	arxiv-cs.LG	2025-08-13
581	LA-EAD: Simple and Effective Methods for Improving Logical Anomaly Detection Capability Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In the field of intelligent manufacturing, image anomaly detection plays a pivotal role in automated product quality inspection. Most existing anomaly detection methods are adept …	Zhixing Li; Zan Yang; Lijie Zhang; Lie Yang; Jiansheng Liu;	Sensors (Basel, Switzerland)	2025-08-13
582	CoBAD: Modeling Collective Behaviors for Human Mobility Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: While traditional anomaly detection methodsprimarily focus on individual movement patterns (e.g., a child should stay athome at night), collective anomaly detection aims to identify irregularities incollective mobility behaviors across individuals (e.g., a child is at homealone while the parents are elsewhere) and remains an underexplored challenge.Unlike individual anomalies, collective anomalies require modelingspatiotemporal dependencies between individuals, introducing additionalcomplexity. To address this gap, we propose CoBAD, a novel model designed tocapture Collective Behaviors for human mobility Anomaly Detection.	Haomin Wen; Shurui Cao; Leman Akoglu;	arxiv-cs.LG	2025-08-13
583	Robust Anomaly Detection in O-RAN: Leveraging LLMs Against Data Manipulation Attacks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We demonstrate that LLM-based xAppsmaintain robust operational performance and are capable of processingmanipulated messages without crashing.	THUSITHA DAYARATNE et. al.	arxiv-cs.CR	2025-08-11
584	Exploring Multi-Modal LLMs for Time Series Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection in time series data is crucial across various domains. Traditional methods often struggle with continuously evolving time series requiring adjustment, whereas …	HAO NIU et. al.	ITISE 2025	2025-08-11
585	LTGS-Net: Local Temporal and Global Spatial Network for Weakly Supervised Video Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Video anomaly detection has an important application value in the field of intelligent surveillance; however, due to the problems of sparse anomaly events and expensive labeling, …	Minghao Li; Xiaohan Wang; Haofei Wang; Min Yang;	Sensors (Basel, Switzerland)	2025-08-08
586	Dual-branch Anomaly Detection Via Feature Embedding and Anomaly Synthesis Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Zihao Chen; Shoubiao Tan;	International Conference on Image Processing and …	2025-08-08
587	A Survey of Streaming Data Anomaly Detection in Network Security Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Cybersecurity has always been a subject of great concern, and anomaly detection has gained increasing attention due to its ability to detect novel attacks. However, network …	Pengju Zhou;	PeerJ. Computer science	2025-08-08
588	AnomalyMoE: Towards A Language-free Generalist Model for Unified Visual Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: These specialized models, tailored for specific anomaly typeslike textural defects or logical errors, typically exhibit limited performancewhen deployed outside their designated contexts. To overcome this limitation,we propose AnomalyMoE, a novel and universal anomaly detection framework basedon a Mixture-of-Experts (MoE) architecture.	ZHAOPENG GU et. al.	arxiv-cs.CV	2025-08-08
589	AutoIAD: Manager-Driven Multi-Agent Collaboration for Automated Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces AutoIAD, a multi-agentcollaboration framework, specifically designed for end-to-end automateddevelopment of industrial visual anomaly detection.	Dongwei Ji; Bingzhang Hu; Yi Zhou;	arxiv-cs.CV	2025-08-07
590	CaPulse: Detecting Anomalies By Tuning in to The Causal Rhythms of Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In thispaper, we leverage causal tools and introduce a new causality-based framework,CaPulse, which tunes in to the underlying causal pulse of time series data toeffectively detect anomalies.	YUTONG XIA et. al.	arxiv-cs.LG	2025-08-06
591	ADSeeker: A Knowledge-Infused Framework for Anomaly Detection and Reasoning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To effectively retrieve and utilize thisknowledge, we introduce the Query Image-Knowledge Retrieval-AugmentedGeneration (Q2K RAG) framework.	KAI ZHANG et. al.	arxiv-cs.IR	2025-08-05
592	Multi-class Image Anomaly Detection for Practical Applications: Requirements and Robust Solutions Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Recent advances in image anomaly detection have extended unsupervisedlearning-based models from single-class settings to multi-class frameworks,aiming to improve efficiency in training time and model storage.	Jaehyuk Heo; Pilsung Kang;	arxiv-cs.CV	2025-08-04
593	Towards Real Unsupervised Anomaly Detection Via Confident Meta-Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose Confident Meta-learning (CoMet), a noveltraining strategy that enables deep anomaly detection models to learn fromuncurated datasets where nominal and anomalous samples coexist, eliminating theneed for explicit filtering.	Muhammad Aqeel; Shakiba Sharifi; Marco Cristani; Francesco Setti;	arxiv-cs.CV	2025-08-04
594	Feature Reconstruction for Anomaly Detection on Directed Multigraphs: A Preprocessing Framework for GNNs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Graph Neural Networks (GNNs) have achieved significant success in anomaly detection across various domains. However, existing GNN approaches face notable challenges when applied …	SICHENG LIANG et. al.	Proceedings of the 31st ACM SIGKDD Conference on Knowledge …	2025-08-03
595	AffinityTune: A Prompt-Tuning Framework for Few-Shot Anomaly Detection on Graphs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Graph anomaly detection (GAD) is a critical task with applications in domains such as networking, finance, and bioinformatics. % However, the scarcity of labeled anomalies and the …	Jingyan Chen; Guanghui Zhu; Guansong Pang; C. Yuan; Yihua Huang;	Proceedings of the 31st ACM SIGKDD Conference on Knowledge …	2025-08-03
596	Global Interpretable Graph-level Anomaly Detection Via Prototype IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save	ZHENYU YANG et. al.	Proceedings of the 31st ACM SIGKDD Conference on Knowledge …	2025-08-03
597	Unsupervised Multivariate Time Series Anomaly Detection By Feature Decoupling in Federated Learning Scenarios Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomalies are usually regarded as data errors or novel patterns previously unseen, which are quite different from most observed data. Accurate detection of anomalies is crucial in …	Yifan He; Xi Ding; Yateng Tang; J. Guan; Shuigeng Zhou;	IEEE Transactions on Artificial Intelligence	2025-08-01
598	Vision Transformer Embedded Video Anomaly Detection Using Attention Driven Recurrence Related Papers Related Patents Related Grants Related Venues Related Experts View Save	UMMAY MARIA MUNA et. al.	Array	2025-08-01
599	Feature-Based Normality Models for Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Detecting previously unseen anomalies in sensor data is a challenging problem for artificial intelligence when sensor-specific and deployment-specific characteristics of the time …	Hui Yie Teh; Kevin I-Kai Wang; Andreas W Kempa-Liehr;	Sensors (Basel, Switzerland)	2025-08-01
600	SYNAD: A Synthetic Object Injection Methodology for Enhanced Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In vision-based anomaly detection, the scarcity of anomalous samples in real-world datasets is one of the main challenges. If none or only a few labeled anomalies are available, …	Karel Rusý; Fabian Seiler; David Breuss; Axel Jantsch;	International Conference on Machine Vision and Applications	2025-08-01
601	Evaluating Effectiveness and Identifying Appropriate Methods for Anomaly Detection in Intelligent Transportation Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection is a crucial application of traffic management to intelligent transportation systems (ITSs). An ITS utilizes predictive models to identify potential problems and …	Qixiu Cheng; Kunming Hong; Kai Huang; Zhiyuan Liu;	IEEE Transactions on Intelligent Transportation Systems	2025-08-01
602	DADN: A Dynamic Anomaly Detection Network for Multivariate Time Series Data of The Industrial Internet of Things Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Industrial Internet of Things (IIoT) faces significant security challenges such as data privacy and vulnerabilities. Unsupervised anomaly detection aims to identify abnormal …	YUSHENG KONG et. al.	IEEE Transactions on Industrial Informatics	2025-08-01
603	Privacy-Preserving Anomaly Detection With Homomorphic Encryption for Industrial Control Systems in Critical Infrastructure Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Critical infrastructure (CI) is essential for societal and economic stability, making it a prime target for cyber threats. Traditional anomaly detection models like LSTM and …	Dahoon Jeong; Y. Kim; Donghoon Shin;	IEEE Embedded Systems Letters	2025-08-01
604	Spatio-Temporal Anomaly Detection for 5G-Clusters: A Multi-Scale Fuzzy Contrastive Learning Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection is an important data-mining task closely related to specific applications. In recent years, spatio-temporal data deriving from various networks has been …	Luo Chao; Yinghua Li; Fengqian Ding; Shao Rui;	IEEE Transactions on Networking	2025-08-01
605	GLASNet: A Global–Local Anomaly Generator and Salient Channel Feature Selector-Based Network for Accurate Few-Shot Industrial Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection of products is of great significance in modern industrial production. However, the current mainstream unsupervised anomaly detection methods based on deep …	Aoshuang Luo; Guojun Wen; Zhuyun Chen; Xingyue Liu;	IEEE Sensors Journal	2025-08-01
606	Automated Graph Anomaly Detection with Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save	JIAQI YU et. al.	Knowl. Based Syst.	2025-08-01
607	MAGE: Multiperiodic Adaptive Graph Evolution Guided Anomaly Detection in Industrial IoT Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Identifying and detecting anomalies in industrial Internet of Things (IIoT) systems is vital for maintaining industrial safety. In IIoT scenarios, various industrial machines …	Weixu Wang; Xiaobo Zhou; Tie Qiu; Lei Wang;	IEEE Transactions on Industrial Informatics	2025-08-01
608	Zero-Shot Anomaly Detection with Dual-Branch Prompt Selection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing ZSAD methods,whether using fixed or learned prompts, struggle under domain shifts becausetheir training data are derived from limited training domains and fail togeneralize to new distributions. In this paper, we introduce PILOT, a frameworkdesigned to overcome these challenges through two key innovations: (1) a noveldual-branch prompt learning mechanism that dynamically integrates a pool oflearnable prompts with structured semantic attributes, enabling the model toadaptively weight the most relevant anomaly cues for each input image; and (2)a label-free test-time adaptation strategy that updates the learnable promptparameters using high-confidence pseudo-labels from unlabeled test data.Extensive experiments on 13 industrial and medical benchmarks demonstrate thatPILOT achieves state-of-the-art performance in both anomaly detection andlocalization under domain shift.	Zihan Wang; Samira Ebrahimi Kahou; Narges Armanfard;	arxiv-cs.CV	2025-08-01
609	ADGAT: Anomaly Detection-based Graph Adversarial Defense Framework Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Youhuizi Li; Y. Wang; Yuyu Yin; Tingting Liang;	Neurocomputing	2025-08-01
610	Anomaly Detection Based on Graph Attention Networks in Semiconductor Manufacturing Processes Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Accurate anomaly detection in multivariate time series sensor data is essential for stabilizing processes and improving yield in semiconductor manufacturing. The intricate …	Qingrui Guo; Shuangwu Chen; Dong Jin; Yao Chen;	2025 6th International Conference on Artificial …	2025-08-01
611	Text-Attributed Graph Anomaly Detection Via Multi-Scale Cross- and Uni-Modal Contrastive Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a novel end-to-end paradigm for text-attributedgraph anomaly detection, named CMUCL.	YIMING XU et. al.	arxiv-cs.LG	2025-08-01
612	Diffusion-Scheduled Denoising Autoencoders for Anomaly Detection in Tabular Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose theDiffusion-Scheduled Denoising Autoencoder (DDAE), a framework that integratesdiffusion-based noise scheduling and contrastive learning into the encodingprocess to improve anomaly detection.	Timur Sattarov; Marco Schreyer; Damian Borth;	arxiv-cs.LG	2025-08-01
613	Anomalous Samples for Few-Shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we tackle the question of utilizing anomaloussamples in training a model for bi- nary anomaly classification.	Aymane Abdali; Bartosz Boguslawski; Lucas Drumetz; Vincent Gripon;	arxiv-cs.LG	2025-07-31
614	Anomaly Detection with Spiking Neural Networks for LHC Physics Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper investigates AutoEncoders builtusing neuromorphic Spiking Neural Networks (SNNs) for this purpose.	Barry M. Dillon; Jim Harkin; Aqib Javed;	arxiv-hep-ph	2025-07-31
615	Unsupervised Machine Learning for Anomaly Detection: A Systematic Review Related Papers Related Patents Related Grants Related Venues Related Experts View Save		International Journal of Electrical and Electronics …	2025-07-31
616	Explainable Deep Anomaly Detection with Sequential Hypothesis Testing for Robotic Sewer Inspection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Traditional inspection methods rely heavily on the manual review ofCCTV footage collected by mobile robots, which is inefficient and susceptibleto human error. To automate this process, we propose a novel systemincorporating explainable deep learning anomaly detection combined withsequential probability ratio testing (SPRT).	Alex George; Will Shepherd; Simon Tait; Lyudmila Mihaylova; Sean R. Anderson;	arxiv-cs.RO	2025-07-30
617	Modified Convolutional Architecture Based Anomaly Detection for Video Surveillance with Mask R-CNN Segmentation Model for Object Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Gudupudi Ravikumar; Malathy Vanniappan; K. Rajkumar;	Signal, Image and Video Processing	2025-07-30
618	Unsupervised Anomaly Detection Method for Electrical Equipment Based on Audio Latent Representation and Parallel Attention Mechanism Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The stable operation of electrical equipment is critical for industrial safety, yet traditional anomaly detection methods often suffer from limitations, such as high resource …	Wei Zhou; Shaoping Zhou; Yikun Cao; Junkang Yang; Hongqing Liu;	Applied Sciences	2025-07-30
619	Cloud Network Anomaly Detection Using Federated Learning and Explainable AI Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Cloud computing environments handle vast amounts of data, making them prime targets for cyber threats such as Distributed Denial-of-Service (DDoS) attacks, ransomware, and insider …	P. Idamakanti;	International Journal on Science and Technology	2025-07-30
620	Multi-View Reconstruction with Global Context for 3D Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Whileexisting methods achieve notable progress, their performance degrades inhigh-precision 3D anomaly detection due to insufficient global information. Toaddress this, we propose Multi-View Reconstruction (MVR), a method thatlosslessly converts high-resolution point clouds into multi-view images andemploys a reconstruction-based anomaly detection framework to enhance globalinformation learning.	Yihan Sun; Yuqi Cheng; Yunkang Cao; Yuxin Zhang; Weiming Shen;	arxiv-cs.CV	2025-07-29
621	NeuCoReClass AD: Redefining Self-Supervised Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To address theselimitations, we introduce NeuCoReClass AD, a self-supervised multi-task timeseries anomaly detection framework that combines contrastive, reconstruction,and classification proxy tasks.	Aitor Sánchez-Ferrera; Usue Mori; Borja Calvo; Jose A. Lozano;	arxiv-cs.LG	2025-07-29
622	An Optimized Anomaly Detection Framework in Industrial Control Systems Through Grey Wolf Optimizer and Autoencoder Integration Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a novel collaborative data processing framework that enhances anomaly detection in ICS by integrating the Grey Wolf Optimizer with Autoencoders.	Muhammad Muzamil Aslam; Liyanage Chandratilak De Silva; Rosyzie Anna Awg Haji Mohd Apong; Ali Tufail;	Scientific reports	2025-07-29
623	Synomaly Noise and Multi-stage Diffusion: A Novel Approach for Unsupervised Anomaly Detection in Medical Images Related Papers Related Patents Related Grants Related Venues Related Experts View Save	YUAN BI et. al.	Medical image analysis	2025-07-26
624	LEAD-Net: Semantic-Enhanced Anomaly Feature Learning for Substation Equipment Defect Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Substation equipment defect detection is a critical aspect of ensuring the reliability and stability of modern power grids. However, existing deep-learning-based detection methods …	LINGHAO ZHANG et. al.	Processes	2025-07-23
625	M3DM-NR: RGB-3D Noisy-Resistant Industrial Anomaly Detection Via Multimodal Denoising IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Existing industrial anomaly detection methods primarily concentrate on unsupervised learning with pristine RGB images. Yet, both RGB and 3D data are crucial for anomaly detection, …	CHENGJIE WANG et. al.	IEEE transactions on pattern analysis and machine …	2025-07-23
626	Unsupervised Anomaly Detection Using Bayesian Flow Networks: Application to Brain FDG PET in The Context of Alzheimer’s Disease Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we focus on Bayesian flownetworks (BFNs), a novel class of generative models, which have not yet beenapplied to medical imaging or anomaly detection.	Hugues Roy; Reuben Dorent; Ninon Burgos;	arxiv-cs.CV	2025-07-23
627	State Estimation and Anomaly Detection of Power System Based on Deep Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: As the intricacy of power systems escalates, conventional anomaly detection techniques struggle to fulfill the demands of contemporary power grids. Deep learning, heralding a new …	Kailin Ma; Dong Wang; Lei Zhang; Dong Chen; Yangyang Yu;	International Conference on Optoelectronics and Information …	2025-07-22
628	Resilient Federated Learning for DDoS Detection with Multi-Krum Aggregation and Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Sajal Saha; M. Sayed; Md. Motiur Rahman; M. Faezipour; Smrity Bhatt;	2025 International Conference on Smart Applications, …	2025-07-22
629	Anomaly Detection in Encrypted Network Traffic Using Self-supervised Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we describe ET-SSL, a new approach for encrypted data anomaly detection which uses self-supervised contrastive learning to identify informative representations in flow level, statistical features like packet length; inter arrival time; flow duration and protocol metadata to Detect anomalies in encrypted network traffic without the need for labelled datasets or payload analysis.	SADAF SATTAR et. al.	Scientific reports	2025-07-22
630	Innovative Image Fraud Detection with Cross-Sample Anomaly Analysis: The Power of LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes CSIAD (Cross-Sample Image Anomaly Detection) by leveraging LLMs to identify logical inconsistencies in similar images.	QIWEN WANG et. al.	acl	2025-07-21
631	Application of Big Data Analysis in Anomaly Detection of Communication Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Aiming at the challenges brought by high-dimensional, time-series and heterogeneous data in anomaly detection of communication networks, this study proposes an anomaly detection …	Liang Yang; Tao Linmi; Yunjin Fu; Feng Zheng; Gaohong Zhao;	Other Conferences	2025-07-21
632	Video Anomaly Detection Based on Both Normal and Anomaly Reconstruction with Siamese Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Traditional autoencoders (AEs) often use only normal data for training in video anomaly detection (VAD) tasks, which makes them unable to better distinguish normal samples from …	Xi Luo; Shifeng Li; Yan Cheng; Xiaoru Liu;	Asia Conference on Computer Vision, Image Processing and …	2025-07-21
633	LogAD: A Multi-Feature Fusion Approach for Log Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the increasing complexity of software systems, log-based anomaly detection has become critical for ensuring system reliability. However, existing methods often suffer from …	GUANGZU WANG et. al.	2025 IEEE International Conference on Joint Cloud Computing …	2025-07-21
634	Towards Explainable Anomaly Detection in Shared Mobility Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents an interpretable anomaly detection frameworkthat integrates multi-source data, including bike-sharing trip records, weatherconditions, and public transit availability.	Elnur Isgandarov; Matteo Cederle; Federico Chiariotti; Gian Antonio Susto;	arxiv-cs.LG	2025-07-21
635	CMHKF: Cross-Modality Heterogeneous Knowledge Fusion for Weakly Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes a novel framework, Cross-Modality Heterogeneous Knowledge Fusion (CMHKF), that integrates cross-modality knowledge from video, audio, and text to improve anomaly detection and localization.	Guohua Wang; Shengping Song; Wuchun He; Yongsen Zheng;	acl	2025-07-21
636	We Need to Rethink Benchmarking in Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Despite the continuous proposal of new anomaly detection algorithms andextensive benchmarking efforts, progress seems to stagnate, with only minorperformance differences between established baselines and new algorithms. Inthis position paper, we argue that this stagnation is due to limitations in howwe evaluate anomaly detection algorithms.	Philipp Röchner; Simon Klüttermann; Franz Rothlauf; Daniel Schlör;	arxiv-cs.LG	2025-07-21
637	TSINR: Capturing Temporal Continuity Via Implicit Neural Representations for Time Series Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: However, the unlabeled anomaly points in training data may cause these reconstruction-based methods to learn and reconstruct anomalous data, resulting in the challenge of capturing normal patterns. In this paper, we propose a time series anomaly detection method based on implicit neural representation (INR) reconstruction, named TSINR, to address this challenge.	MENGXUAN LI et. al.	kdd	2025-07-20
638	How to Use Graph Data in The Wild to Help Graph Anomaly Detection? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Yet, when the available data is insufficient, capturing the normal distribution accurately and comprehensively becomes difficult. To overcome this limitation, we propose to utilize external graph data (i.e., graph data in the wild) to help anomaly detection tasks.	YUXUAN CAO et. al.	kdd	2025-07-20
639	Residual-Based Hybrid Deep Learning Model for Anomaly Detection in Wireless Sensor Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Wireless Sensor Networks (WSNs) are increasingly deployed in environmental monitoring, smart buildings, and industrial IoT applications, where continuous and accurate data …	Rosamma K S;	2025 Advanced Computing and Communication Technologies for …	2025-07-18
640	Unmasking Performance Gaps: A Comparative Study of Human Anonymization and Its Effects on Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present a comprehensive analysis ofanomaly detection performance under four human anonymization techniques,including blurring, masking, encryption, and avatar replacement, applied to theUCF-Crime dataset.	Sara Abdulaziz; Egor Bondarev;	arxiv-cs.CV	2025-07-18
641	Anomaly Detection with Domain Specific Shapelet Learning for Sucker Rod Pump System Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes an unsupervised end-to-end learning algorithm designed for SRPS anomaly detection, denoted Anomaly Detection with Domain-specific Shapelet Learning algorithm (AD-DSL).	Xiangyu Li; Zhupei Liao; Chunhua Yuan;	Scientific reports	2025-07-18
642	Text-ADBench: Text Anomaly Detection Benchmark Based on LLMs Embedding Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work performs a comprehensiveempirical study and introduces a benchmark for text anomaly detection,leveraging embeddings from diverse pre-trained language models across a widearray of text datasets.	Feng Xiao; Jicong Fan;	arxiv-cs.CL	2025-07-16
643	Digital Twin-driven Anomaly Detection in Multimodel Combining Fusion Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The application of digital twin technology in the field of intelligent manufacturing is gradually increasing, and this paper proposes a multi-model combining fusion physical …	Gaoyang Liu; Pan Liu;	Conference on Image, Signal Processing, and Pattern …	2025-07-16
644	A Unified Framework for Anomaly Detection and Root Cause Analysis in Microservice Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Modern software applications increasingly rely on microservice architectures for scalability, flexibility, and rapid deployment. However, this architectural paradigm introduces …	Oliver Meyer; Eric Johnson; Jacob Brown;	Computer Life	2025-07-15
645	Hyperbolic Geometry Enhanced Feature Filtering Network for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents HADNet, a hyperbolic space-based anomaly detection method.	Yanjun Feng; Jun Liu; Yonggang Gai;	Scientific reports	2025-07-15
646	BenchReAD: A Systematic Benchmark for Retinal Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Inspired by the memory bank mechanismsin one-class supervised learning, we propose NFM-DRA, which integrates DRA witha Normal Feature Memory to mitigate the performance degradation, establishing anew SOTA.	Chenyu Lian; Hong-Yu Zhou; Zhanli Hu; Jing Qin;	arxiv-cs.CV	2025-07-14
647	VJDNet: A Simple Variational Joint Discrimination Network for Cross-Image Hyperspectral Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: To enhance the generalization of networks and avoid redundant training efforts, cross-image hyperspectral anomaly detection (HAD) based on deep learning has been gradually studied …	SHIQI WU et. al.	Remote Sensing	2025-07-14
648	Stereo-based 3D Anomaly Object Detection for Autonomous Driving: A New Dataset and Baseline Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Thispaper proposes a Stereo-based 3D Anomaly object Detection (S3AD) algorithm,which decouples the training strategy of 3D and 2D to release thegeneralization ability for arbitrary 3D foreground detection, and proposes ananomaly scoring algorithm based on foreground confidence prediction, achievingtarget-level anomaly scoring.	Shiyi Mu; Zichong Gu; Hanqi Lyu; Yilin Gao; Shugong Xu;	arxiv-cs.CV	2025-07-12
649	Anomaly Detection in Nuclear Power Production Based on Neural Normal Stochastic Process Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: To ensure the safety of nuclear power production, nuclear power plants deploy numerous sensors to monitor various physical indicators during production, enabling the early …	LINYU LIU et. al.	Sensors (Basel, Switzerland)	2025-07-12
650	Real-Time Decorrelation-Based Anomaly Detection for Multivariate Time Series Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection (AD) plays a vital role across a wide range of real-worlddomains by identifying data instances that deviate from expected patterns,potentially signaling critical …	Amirhossein Sadough; Mahyar Shahsavari; Mark Wijtvliet; Marcel van Gerven;	arxiv-cs.LG	2025-07-10
651	Beyond Log Parsers: A Scalable AI-Driven Framework for Efficient Log Anomaly Detection in Software Engineering Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Log anomaly detection is critical for ensuring software system reliability and security, yet challenges persist in log parser dependency, small-scale dataset applicability, and …	YICHENG SUN et. al.	2025 IEEE 49th Annual Computers, Software, and Applications …	2025-07-08
652	What ZTF Saw Where Rubin Looked: Anomaly Hunting in DR23 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present results from the SNAD VIII Workshop, during which we conducted thefirst systematic anomaly search in the ZTF fields also observed by LSSTComCamduring Rubin Scientific Pipeline commissioning.	MARIA V. PRUZHINSKAYA et. al.	arxiv-astro-ph.IM	2025-07-08
653	Robust Spectral Anomaly Detection in EELS Spectral Images Via 3D Convolutional Variational Autoencoders Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: A 3D Convolutional Variational Autoencoder (3D-CVAE) is introduced for automated anomaly detection in electron energy-loss spectroscopy spectrum imaging (EELS-SI) data. This …	Seyfal Sultanov; R A W Ayyubi; James P Buban; Robert F Klie;	Small (Weinheim an der Bergstrasse, Germany)	2025-07-06
654	Dealing with Uncertainty in Contextual Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose a novel framework for CAD,normalcy score (NS), that explicitly models both the aleatoric and epistemicuncertainties.	Luca Bindini; Lorenzo Perini; Stefano Nistri; Jesse Davis; Paolo Frasconi;	arxiv-cs.LG	2025-07-06
655	Optimized Two-Stage Anomaly Detection and Recovery in Smart Grid Data Using Enhanced DeBERTa-v3 Verification System Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study presents an optimized two-stage anomaly detection and recovery system combining an enhanced TimerXL detector with a DeBERTa-v3-based verification and recovery mechanism.	Xiao Liao; Wei Cui; Min Zhang; Aiwu Zhang; Pan Hu;	Sensors (Basel, Switzerland)	2025-07-05
656	Anomaly Detection in Cloud Computing Workloads Based on Resource Usage Related Papers Related Patents Related Grants Related Venues Related Experts View Save	A. Jahani; Paria Jourabchi Amirkhizi;	J. Netw. Syst. Manag.	2025-07-05
657	ML-Enhanced AES Anomaly Detection for Real-Time Embedded Security Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose a comprehensive frameworkthat enhances AES-128 encryption security through controlled anomaly injectionand real-time anomaly detection using both statistical and machine learning(ML) methods.	Nishant Chinnasami; Rye Stahle-Smith; Rasha Karakchi;	arxiv-cs.CR	2025-07-05
658	A Hybrid Unsupervised-weakly Supervised Method for Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Akhrorjon Akhmadjon Ugli Rakhmonov; Bahar Amirian Varnousefaderani; Jeonghong Kim;	Pattern Analysis and Applications	2025-07-02
659	Towards Foundation Auto-Encoders for Time-Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce FAE (FoundationAuto-Encoders), a foundation generative-AI model for anomaly detection intime-series data, based on Variational Auto-Encoders (VAEs).	Gastón García González; Pedro Casas; Emilio Martínez; Alicia Fernández;	arxiv-cs.LG	2025-07-02
660	OoDDINO: A Multi-level Framework for Anomaly Segmentation on Complex Road Scenes Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly segmentation aims to identify Out-of-Distribution (OoD) anomalous objects within images. Existing pixel-wise methods typi- cally assign anomaly scores individually and …	YUXING LIU et. al.	Proceedings of the 33rd ACM International Conference on …	2025-07-02
661	OoDDINO:A Multi-level Framework for Anomaly Segmentation on Complex Road Scenes Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we introduce OoDDINO, a novelmulti-level anomaly segmentation framework designed to address theselimitations through a coarse-to-fine anomaly detection strategy.	YUXING LIU et. al.	arxiv-cs.CV	2025-07-02
662	Exploring A Hybrid Deep Learning Approach for Anomaly Detection in Mental Healthcare Provider Billing: Addressing Label Scarcity Through Semi-Supervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study explores a hybrid deep learning approachcombining Long Short-Term Memory (LSTM) networks and Transformers, withpseudo-labeling via Isolation Forests (iForest) and Autoencoders (AE).	Samirah Bakker; Yao Ma; Seyed Sahand Mohammadi Ziabari;	arxiv-cs.LG	2025-07-02
663	Enhancing Machine Learning-based Anomaly Detection for IoT Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save	AbedlRahman Almodawar; Ashraf Ahmad;	2025 16th International Conference on Information and …	2025-07-01
664	Partially-Supervised Graph Derivation Network With Meta-Learning for Time-Series Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Time-series anomaly detection is essential in various fields, such as industrial monitoring, cybersecurity, and finance. Traditional supervised methods often face challenges due …	Sanli Zhu; Yuan Li; Kang Xu; Junjun Xu;	IEEE Internet of Things Journal	2025-07-01
665	MLAD: A Multi-Task Learning Framework for Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection in multivariate time series is a critical task across a range of real-world domains, such as industrial automation and the internet of things. These environments …	Kunqi Li; Zhiqin Tang; Shuming Liang; Zhidong Li; Bin Liang;	Sensors (Basel, Switzerland)	2025-07-01
666	Multi-view Graph Anomaly Detection Via Subgraph Anomaly Augmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Save	FU LIN et. al.	Neurocomputing	2025-07-01
667	Biorthogonal Tunable Wavelet Unit with Lifting Scheme in Convolutional Neural Network Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work introduces a novel biorthogonal tunable wavelet unit constructedusing a lifting scheme that relaxes both the orthogonality and equal filterlength constraints, providing greater flexibility in filter design.	An Le; Hung Nguyen; Sungbal Seo; You-Suk Bae; Truong Nguyen;	arxiv-cs.CV	2025-07-01
668	TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection [E, A & B] IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Despite decades of research on time-series anomaly detection, the effectiveness of existing anomaly detectors remains constrained to specific domains – a model that performs well …	Qinghua Liu; Seunghak Lee; John Paparrizos;	Proc. VLDB Endow.	2025-07-01
669	Generative Adversarial Networks-enabled Anomaly Detection Systems: A Survey IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save	UMER SAEED et. al.	Expert Systems with Applications	2025-07-01
670	Anomaly Detection Based on Vision Transformer Model and Texture Features Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Mohammed Lahraichi; Abdelhafid Berroukham; Khalid Housni;	Journal of Computer Science	2025-07-01
671	LogDLR: Unsupervised Cross-System Log Anomaly Detection Through Domain-Invariant Latent Representation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Log anomaly detection aims to discover abnormal events from massive log data to ensure the security and reliability of software systems. However, due to the heterogeneity of log …	JUNWEI ZHOU et. al.	IEEE Transactions on Dependable and Secure Computing	2025-07-01
672	Attention-GANomaly: Unsupervised Hyperspectral Anomaly Detection Via Attention Based GANs Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Mohammad Bahmanpour; D. Abbasi-Moghadam; Alireza Sharifi;	Infrared Physics & Technology	2025-07-01
673	CoLA: Model Collaboration for Log-based Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Log-based anomaly detection plays a crucial role in ensuring the reliability of systems. While deep learning-based small detection models (SDMs) are efficient, the large language …	XUHAN ZHU et. al.	Proc. VLDB Endow.	2025-07-01
674	Anomaly Detection Method for Hydropower Units Based on KSQDC-ADEAD Under Complex Operating Conditions Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The safe and stable operation of hydropower units, as core equipment in clean energy systems, is crucial for power system security. However, anomaly detection under complex …	TONGQIANG YI et. al.	Sensors (Basel, Switzerland)	2025-06-30
675	Multi-Class Anomaly Detection in Network Intrusion Detection Using Variational Autoencoder Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Azhar F. Al-zubidi; A. K. Farhan;	International Journal of Safety and Security Engineering	2025-06-30
676	Zero-shot GOOSE Anomaly Detection Via Multi-gate Mixture-of-Experts with Pre-Trained Large Language Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Detecting anomalies in smart grids is vital to safeguarding systems from attacks and failures. As critical components in IEC 61850-based substation communication, Generic …	Yi Li; Mingfeng Fan; Guo Chen; Chaojie Li; Biplab Sikdar;	2025 IEEE Kiel PowerTech	2025-06-29
677	DCCopGAN: Deep Convolutional Copula-GAN for Unsupervised Multi-Sensor Anomaly Detection in Industrial Gearboxes Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The gearbox, a key transmission device in industrial applications, can cause severe vibrations or failures when anomalies occur. With increasing industrial automation complexity, …	Bowei Ge; Ye Li; Guangqiang Yin;	Electronics	2025-06-29
678	XLSTMAD: A Powerful XLSTM-based Method for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Despite its growing popularity, no prior work has explored xLSTMfor anomaly detection. In this work, we fill this gap by proposing xLSTMAD, thefirst anomaly detection method that integrates a full encoder-decoder xLSTMarchitecture, purpose-built for multivariate time series data.	Kamil Faber; Marcin Pietroń; Dominik Żurek; Roberto Corizzo;	arxiv-cs.LG	2025-06-28
679	Research on Anomaly Detection Algorithm System for Financial Transaction Data Processing Based on Deep Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: This paper studies an anomaly detection algorithm system for financial transaction data processing based on deep learning. First, this paper proposes an anomaly detection …	Yuan Li; N. Wu; Donghui Tang; Xiuliang Zhang;	2025 IEEE 3rd International Conference on Image Processing …	2025-06-28
680	Unsupervised Brain MRI Anomaly Detection Via Inter-Realization Channels Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Accurate anomaly detection in brain Magnetic Resonance Imaging (MRI) is crucial for early diagnosis of neurological disorders, yet remains a significant challenge due to the high …	Hussain Ahmad Madni; Hafsa Shujat; Axel De Nardin; Silvia Zottin; Gian Luca Foresti;	International journal of neural systems	2025-06-27
681	FedSW-TSAD: SWGAN-Based Federated Time Series Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: As distributed sensing technologies evolve, the collection of time series data is becoming increasingly decentralized, which introduces serious challenges for both model training …	XIUXIAN ZHANG et. al.	Sensors (Basel, Switzerland)	2025-06-27
682	Anomaly Detection Based on Positive and Negative Phase Angle Light Intensity Templates for Satellites Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: During satellite operations, abnormal changes may occur due to adjustments in the detection targets or the charging of solar panels. To address the complex attitude recognition …	Yi Tang; Shuhua Wang; Chen Qi; Jiazhi Wang;	International Conference on Information Optics and …	2025-06-26
683	MTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scale Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce mTSBench, the largest benchmark to date forMTS-AD and unsupervised model selection, spanning 344 labeled time seriesacross 19 datasets and 12 diverse application domains.	Xiaona Zhou; Constantin Brif; Ismini Lourentzou;	arxiv-cs.LG	2025-06-26
684	Demeaned Sparse: Efficient Anomaly Detection By Residual Estimate Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Frequency-domain image anomaly detection methods can substantially enhance anomaly detection performance, however, they still lack an interpretable theoretical framework to guarantee the effectiveness of the detection process. We propose a novel test to detect anomalies in structural image via a Demeaned Fourier transform (DFT) under factor model framework, and we proof its effectiveness.	YIFAN FANG et. al.	icml	2025-06-25
685	Towards A Unified Framework of Clustering-based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Consequently, their collective potential to enhance anomaly detection performance remains largely untapped. To bridge this gap, in this paper, we propose a novel probabilistic mixture model for anomaly detection to establish a theoretical connection among representation learning, clustering, and anomaly detection.	ZEYU FANG et. al.	icml	2025-06-25
686	Ex-VAD: Explainable Fine-grained Video Anomaly Detection Based on Visual-Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing methods focus mainly on coarse-grained detection, lacking anomaly explanations. To address these challenges, we propose Ex-VAD, an Explainable Fine-grained Video Anomaly Detection approach that combines fine-grained classification with detailed explanations of anomalies.	CHAO HUANG et. al.	icml	2025-06-25
687	When Every Millisecond Counts: Real-Time Anomaly Detection Via The Multimodal Asynchronous Hybrid Network Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce real-time anomaly detection for autonomous driving, prioritizing both minimal response time and high accuracy.	DONG XIAO et. al.	icml	2025-06-25
688	Benchmarking Unsupervised Strategies for Anomaly Detection in Multivariate Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, weinvestigate transformer-based approaches for time series anomaly detection,focusing on the recently proposed iTransformer architecture.	Laura Boggia; Rafael Teixeira de Lima; Bogdan Malaescu;	arxiv-cs.LG	2025-06-25
689	A Digital Model of A Ventilation System for Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: This paper presents a digital model based on a Finite Volume Method (FVM), representing a simple ventilation system. The physical model solves the Euler equations for air flow in …	Bartosz Chaber; Patryk Chaber;	2025 Progress in Applied Electrical Engineering (PAEE)	2025-06-23
690	Learning High-Quality Latent Representations for Anomaly Detection and Signal Integrity Enhancement in High-Speed Signals Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To achievethis, we propose a joint training framework that integrates an autoencoder witha classifier to learn more distinctive latent representations by focusing onvalid data features.	MUHAMMAD USAMA et. al.	arxiv-cs.LG	2025-06-23
691	Quantitative Benchmarking of Anomaly Detection Methods in Digital Pathology Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, the unique characteristics of pathology images,such as their large size, multi-scale structures, stain variability, andrepetitive patterns, introduce new challenges that current anomaly detectionalgorithms struggle to address. In this quantitative study, we benchmark over20 classical and prevalent anomaly detection methods through extensiveexperiments.	CAN CUI et. al.	arxiv-eess.IV	2025-06-23
692	A Systematic Survey: Role of Deep Learning-based Image Anomaly Detection in Industrial Inspection Contexts IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Industrial automation is rapidly evolving, encompassing tasks from initial assembly to final product quality inspection. Accurate anomaly detection is crucial for ensuring the …	Vinita Shukla; Amit Shukla; Surya Prakash S K; Shraddha Shukla;	Frontiers in robotics and AI	2025-06-23
693	Consensus-Based Feature Selection and Classifier Benchmarking for Network Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Efficient anomaly detection in network traffic is essential for securing modern digital infrastructures. This study presents a comprehensive comparative analysis of six feature …	Rifqy Hakimi; Wervyan Shalannanda; H. Heriansyah;	Journal of Engineering and Scientific Research	2025-06-22
694	Online Detection of Anomalies in Temporal Knowledge Graphs with Interpretability Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: Moreover, these methods falter in adapting to pattern changes and semantic drifts resulting from knowledge updates. To tackle these challenges, we introduce AnoT, an efficient TKG summarization method tailored for interpretable online anomaly detection in TKGs.	Jiasheng Zhang; Rex Ying; Jie Shao;	sigmod	2025-06-22
695	Pluto: Sample Selection for Robust Anomaly Detection on Polluted Log Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we thus propose a robust log anomaly detection framework, PlutoNOSPACE, that automatically selects a clean representative sample subset of the polluted log sequence data to train a Transformer-based anomaly detection model.	LEI MA et. al.	sigmod	2025-06-22
696	Agree to Disagree: Robust Anomaly Detection with Noisy Labels Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Sample selection often fails to separate sufficiently many clean anomaly samples from noisy ones, while label refurbishment erroneously refurbishes marginal clean samples. To overcome these limitations, we design Unity, the first learning from noisy labels (LNL) approach for anomaly detection that elegantly leverages the merits of both sample selection and label refurbishment to iteratively prepare a diverse clean sample set for network training.	DENNIS M. HOFMANN et. al.	sigmod	2025-06-22
697	Hybrid Forecasting-Anomaly Detection Approach for Smart Building Energy Monitoring Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Smart buildings rely on continuous monitoring and data-driven decision-making to optimize energy consumption, reduce operational costs, and detect faults early. In this context, …	Morcos Metry; Saima Sharma; S. Allawi; Robert S. Balog; Rabab Benotsmane;	2025 IEEE 34th International Symposium on Industrial …	2025-06-20
698	Advancing Cloud Anomaly Detection: A Machine Learning Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Cloud computing has transformed modern IT architecture by enabling scalable and flexible computing resources. As the popularity of cloud-based services evolves, so do security …	Aarti Punia; Preeti Gulia; N. S. Gill;	2025 5th International Conference on Intelligent …	2025-06-20
699	Noise Fusion-based Distillation Learning for Anomaly Detection in Complex Industrial Environments Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a novel anomaly detection andlocalization method specifically designed to handle inputs with perturbativepatterns.	JIAWEN YU et. al.	arxiv-cs.RO	2025-06-19
700	Monitoring Data for Anomaly Detection in Cloud-Based Systems: A Systematic Mapping Study Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Context: Anomaly detection is crucial for maintaining cloud-based software systems, as it enables early identification and resolution of unexpected failures. Given rapid and …	Adha Hrusto; N. Ali; Emelie Engström; Yuqing Wang;	ACM Transactions on Software Engineering and Methodology	2025-06-17
701	Latent Representation Learning for Attributed Graph Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection in attributed graph data has been widely applied in real applications. However, the intricate topology of graph data, high-dimensional attributes, and class …	Shichao Zhang; Penghui Xi; Mengqi Jiang; Guixian Zhang; Debo Cheng;	ACM Transactions on Knowledge Discovery from Data	2025-06-17
702	Enhancing Endpoint Security Through AI Powered Anomaly Detection in Endpoint Logs Using Local Outlier Factor (LOF) Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In today’s digital era cybersecurity landscape, endpoint security remains a critical concern due to the increasing sophistication of cyber threats. This study explores anomaly …	A. Mohideen; P. Krishna Sai; Y. S. Basha; S. Sohel; Y. V. Reddy;	2025 6th International Conference on Intelligent …	2025-06-17
703	TEAD: Trust-enhanced Anomaly Detection Framework for Intrusion Detection in IoT-enabled Wireless Sensor Networks (WSNs) Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Raja Waseem Anwer; Mohammad Abrar; Abdul Salam; Faizan Ullah;	Wireless Networks	2025-06-16
704	Evaluation of The Feasibility of Anomaly Detection for Dose Management in PET Examinations Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Owing to the revision of the Medical Care Act in 2020, managing and recording radiation doses in PET-CT examinations have become mandatory. In this study, we investigated …	YUSUKE FUKUI et. al.	Annals of nuclear medicine	2025-06-16
705	Unsupervised Distributed Anomaly Detection Framework for IoT in Edge AI Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection of sensor data is crucial to ensure the stability and effectiveness of Internet of Things (IoT) system. The task requires high accuracy and low latency, which …	Xingguo Jiang; Chang Lu; Hong Luo; Yan Sun;	IEEE Internet of Things Journal	2025-06-15
706	Similarity Augmented Incremental Learning-Based Flight Data Anomaly Detection Method for UAV Dynamic Conditions Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In response to the high accident rate associated with large-scale unmanned aerial vehicle (UAV) deployment, the prediction-based anomaly detection method has emerged as an …	Shouqiang Kang; Chuanjin Han; Benkuan Wang; Yuan Wang; Datong Liu;	IEEE Sensors Journal	2025-06-15
707	Anomaly Detection in IoT Networks Using Federated Machine Learning Approaches Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The rapid growth of Internet of Things (IoT) networks has brought forth new challenges in ensuring the security and reliability of devices and data. Anomaly detection in IoT …	R. Vidhya; D. Lognathan; Saranya S; P.N. Periyasamy; S. Sumathi;	International Journal of Computational and Experimental …	2025-06-14
708	A Survey of Deep Learning for Industrial Visual Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Zhuo Li; Yuhao Yan; Xiangheng Wang; Yifei Ge; Lin Meng;	Artif. Intell. Rev.	2025-06-14
709	Industrial Image Anomaly Detection Via Synthetic-Anomaly Contrastive Distillation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Industrial image anomaly detection plays a critical role in intelligent manufacturing by automatically identifying defective products through visual inspection. While unsupervised …	Junxian Li; Mingxing Li; Shucheng Huang; Gang Wang; Xinjing Zhao;	Sensors (Basel, Switzerland)	2025-06-13
710	Meta-Learning Approach for Adaptive Anomaly Detection from Multi-Scenario Video Surveillance Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Video surveillance is widely used in different areas like roads, malls, education, industries, retail, parks, bus stands, and restaurants, each presenting distinct anomaly …	Deepak Kumar Singh; D. Pant; Ganesh Gautam; Bhanu Shrestha;	Applied Sciences	2025-06-13
711	Anomaly Detection for Sensing Security Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Various approaches in the field of physical layer security involve anomaly detection, such as physical layer authentication, sensing attacks, and anti-tampering solutions. Depending on the context in which these approaches are applied, anomaly detection needs to be computationally lightweight, resilient to changes in temperature and environment, and robust against phase noise.	Stefan Roth; Aydin Sezgin;	arxiv-cs.IT	2025-06-12
712	Unsupervised Hierarchical Denoising Guided Student-Teacher Framework for Battery Spot Welding Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Accurate detection of battery spot welding quality is crucial for ensuring the safety and reliability of batteries. However, traditional visual detection methods are limited in …	Yingwen Chen; Kengcan Feng; Ying Xu; Tianlei Wang; Yikui Zhai;	2025 IEEE International Conference on Computational …	2025-06-12
713	Performance Evaluation of Anomaly Detection with A Novel Battery Spot Welding Anomaly Dataset Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Battery spot weld defect detection is a critical aspect of ensuring battery quality. Traditional manual inspection methods are not only inefficient but also prone to omissions and …	YINGWEN CHEN et. al.	International Conference on Signal Processing and Neural …	2025-06-11
714	Privacy Protection Anomaly Detection in Smart Grids Based on Combined PHE and TFHE Homomorphic Encryption Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the growing scale and complexity of smart grids, ensuring both effective anomaly detection and robust privacy protection has become increasingly critical. This paper proposes …	YONGCAI XIAO et. al.	Electronics	2025-06-11
715	ADDAEIL: Anomaly Detection with Drift-Aware Ensemble-Based Incremental Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Time series anomaly detection in streaming environments faces persistent challenges due to concept drift, which gradually degrades model reliability. In this paper, we propose …	Danlei Li; Nirmal Nair; Kevin I.-Kai Wang;	Algorithms	2025-06-11
716	FusedVision: A Knowledge-Infusing Approach for Practical Anomaly Detection in Real-World Surveillance Videos Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Object-centric approaches have gained attention as effective one-class classification methods for detecting anomalies in videos. These approaches rely on using an object detector …	KHALED DAWOUD et. al.	2025 IEEE/CVF Conference on Computer Vision and Pattern …	2025-06-11
717	Robust AD: A Real World Benchmark Dataset for Robustness in Industrial Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Successful deployment of anomaly detection algorithms in real-world industrial settings, particularly for defect detection tasks, is often hampered by performance degradation due …	Latha Pemula; Dongqing Zhang; O. Dabeer;	2025 IEEE/CVF Conference on Computer Vision and Pattern …	2025-06-11
718	Conditional Diffusion Models for Guided Anomaly Detection in Brain Images Using Fluid-driven Anomaly Randomization Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we introduce a novel conditional diffusion model framework for anomaly detection and healthy image reconstruction in brain MRI.	Ana Lawry Aguila; Peirong Liu; Oula Puonti; Juan Eugenio Iglesias;	arxiv-eess.IV	2025-06-11
719	Enhancing IoT Data Analytics with Deep Learning-based Anomaly Detection and Real-time Processing on Edge Devices Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The Internet of Things (IoT) is an essential component of the digital age, particularly in ensuring reliable and efficient operations as well as the timely and precise recognition …	Rong Wang;	Journal of Computational Methods in Sciences and Engineering	2025-06-10
720	HomographyAD: Deep Anomaly Detection Using Self Homography Learning Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, the existing anomaly detection works have a limitation of showing good performance for fully-aligned datasets only, unlike real-world industrial environments. To solve this limitation, we propose HomographyAD, a novel deep anomaly detection methodology based on the ImageNet-pretrained network, which is specially designed for actual industrial dataset.	Jongyub Seok; Chanjin Kang;	arxiv-cs.CV	2025-06-10
721	A Unified Latent Schrödinger Bridge Diffusion Model for Unsupervised Anomaly Detection and Localization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection and localization remain pivotal challenges in computer vision, with applications ranging from industrial inspection to medical diagnostics. While current …	Shilhora Akshay; Niveditha Lakshmi Narasimhan; Jacob George; Vineeth N. Balasubramanian;	2025 IEEE/CVF Conference on Computer Vision and Pattern …	2025-06-10
722	Anomaly Detection and Generation with Diffusion Models: A Survey Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this survey, we comprehensively review anomaly detection and generation with diffusion models (ADGDM), presenting a tutorial-style analysis of the theoretical foundations and practical implementations and spanning images, videos, time series, tabular, and multimodal data.	YANG LIU et. al.	arxiv-cs.LG	2025-06-10
723	Label-independent Framework for Objective Evaluation of Cosmetic Outcome in Breast Cancer Related Papers Related Patents Related Grants Related Venues Related Experts View Save	SANGJOON PARK et. al.	Artificial intelligence in medicine	2025-06-09
724	A New Anomaly Detection Approach Based on Siamese Network with Fast Gradient Sign Algorithm for Fault Diagnosis of Rolling Bearing Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection is a crucial step in rolling bearing health management. Recently, unsupervised learning models driven solely by normal data for anomaly detection have received …	Chen Jia; Si Nan; Hong Jiang; Yonggang Xu; Kun Zhang;	Engineering Research Express	2025-06-09
725	Multi-Model Machine Learning Approaches for Fault and Anomaly Detection in Petroleum Product Distribution: A Comparison Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Maintaining the integrity of petroleum transportation is essential for operational safety and efficiency. Substantial issues arise from faults in fuel transportation systems, …	E. Meçe; Jedina Xure; Paola Caushi; A. Bozzi; I. Shinko;	2025 20th Annual System of Systems Engineering Conference …	2025-06-08
726	Track Any Anomalous Object:A Granular Video Anomaly Detection Pipeline Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Albeit existing methods have primarily focused on detecting anomalous objects in videos–either by identifying anomalous frames or objects–they often neglect finer-grained analysis, such as anomalous pixels, which limits their ability to capture a broader range of anomalies. To address this challenge, we propose an innovative VAD framework called \underline T rack Any \underline A nomalous \underline O bject (\textit TAO ), which introduces a Granular Video Anomaly Detection Framework that, for the first time, integrates the detection of multiple fine-grained anomalous objects into a unified framework.	YUZHI HUANG et. al.	cvpr	2025-06-07
727	A Unified Latent Schrodinger Bridge Diffusion Model for Unsupervised Anomaly Detection and Localization Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This work introduces the Latent Anomaly Schrodinger Bridge (LASB), a unified unsupervised anomaly detection model that operates entirely in the latent space without requiring additional networks or custom modifications.	Shilhora Akshay; Niveditha Lakshmi Narasimhan; Jacob George; Vineeth N Balasubramanian;	cvpr	2025-06-07
728	Towards Visual Discrimination and Reasoning of Real-World Physical Dynamics: Physics-Grounded Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Humans detect real-world object anomalies by perceiving, interacting, and reasoning based on object-conditioned physical knowledge. The long-term goal of Industrial Anomaly …	WENQIAO LI et. al.	cvpr	2025-06-07
729	Correcting Deviations from Normality: A Reformulated Diffusion Model for Multi-Class Unsupervised Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: This paper introduces a reformulation of the standard diffusion model geared toward selective region alteration, allowing the accurate identification of anomalies.	Farzad Beizaee; Gregory A. Lodygensky; Christian Desrosiers; Jose Dolz;	cvpr	2025-06-07
730	Towards Training-free Anomaly Detection with Vision and Language Foundation Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: In this paper, we introduce LogSAD, a novel multi-modal framework that requires no training for both Logical and Structural Anomaly Detection.	Jinjin Zhang; Guodong Wang; Yizhou Jin; Di Huang;	cvpr	2025-06-07
731	DFM: Differentiable Feature Matching for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, they can only achieve an inferior feature representation for anomaly detection because the feature extraction and matching modules are separately trained. To address these issues, we propose a Differentiable Feature Matching (DFM) framework for joint optimization of the feature extractor and the matching head.	SHENG WU et. al.	cvpr	2025-06-07
732	Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: They fail to capture the wide range of anomaly types, as single sensors are often constrained to either external appearance, geometric structure, or internal properties. To overcome these challenges, we introduce MulSen-AD, the first high-resolution, multi-sensor anomaly detection dataset tailored for industrial applications.	WENQIAO LI et. al.	cvpr	2025-06-07
733	AA-CLIP: Enhancing Zero-Shot Anomaly Detection Via Anomaly-Aware CLIP IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: While CLIP shows promise for zero-shot AD tasks due to its strong generalization capabilities, its inherent Anomaly-Unawareness leads to limited discrimination between normal and abnormal features. To address this problem, we propose Anomaly-Aware CLIP (AA-CLIP), which enhances CLIP’s anomaly discrimination ability in both text and visual spaces while preserving its generalization capability.	WENXIN MA et. al.	cvpr	2025-06-07
734	Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To facilitate research in AD & reasoning, we establish the first visual instruction tuning dataset, Anomaly-Instruct-125k, and the evaluation benchmark, VisA-D&R. Through investigation with our benchmark, we reveal that current MLLMs like GPT-4o cannot accurately detect and describe fine-grained anomalous details in images. To address this, we propose Anomaly-OneVision (Anomaly-OV), the first specialist visual assistant for ZSAD and reasoning.	Jiacong Xu; Shao-Yuan Lo; Bardia Safaei; Vishal M. Patel; Isht Dwivedi;	cvpr	2025-06-07
735	Anomize: Better Open Vocabulary Video Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The second challenge is categorization confusion, where novel anomalies are often misclassified as visually similar base instances. To address these challenges, we explore supplementary information from multiple sources to mitigate detection ambiguity by leveraging multiple levels of visual data alongside matching textual information.	FEI LI et. al.	cvpr	2025-06-07
736	Dinomaly: The Less Is More Philosophy in Multi-Class Unsupervised Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: In this paper, we present Dinomaly, a minimalist reconstruction-based anomaly detection framework that harnesses pure Transformer architectures without relying on complex designs, additional modules, or specialized tricks.	JIA GUO et. al.	cvpr	2025-06-07
737	An Explainable Unsupervised Learning Approach for Anomaly Detection on Corneal in Vivo Confocal Microscopy Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: confocal microscopy (IVCM) is a crucial imaging modality for assessing corneal diseases, yet distinguishing pathological features from normal variations remains challenging due to …	NINGNING TANG et. al.	Frontiers in bioengineering and biotechnology	2025-06-06
738	Dynamic Graph Contrastive Learning for Multivariate Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Anqin Zhang; Peng Chen; Yufei Gu; Ting Zhang;	J. Supercomput.	2025-06-05
739	End-to-End Abnormal Subgraph Detection Via Subgraph-Level Contrastive Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Abnormal subgraph (AS) detection plays a significant role in ensuring the security of many high-impact domains. Unlike node anomaly detection, identifying subgraph anomalies is …	ZHEN PENG et. al.	IEEE transactions on neural networks and learning systems	2025-06-05
740	Intelligent System Log Analysis for Cybersecurity: Implementing Advanced Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Puspita Dash; B. S; Ragul S; S. S;	2025 International Conference on Emerging Technologies in …	2025-06-05
741	Track Any Anomalous Object: A Granular Video Anomaly Detection Pipeline Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Although existing methods have primarily focused on detecting anomalous objects in videos — either by identifying anomalous frames or objects — they often neglect finer-grained analysis, such as anomalous pixels, which limits their ability to capture a broader range of anomalies. To address this challenge, we propose a new framework called Track Any Anomalous Object (TAO), which introduces a granular video anomaly detection pipeline that, for the first time, integrates the detection of multiple fine-grained anomalous objects into a unified framework.	YUZHI HUANG et. al.	arxiv-cs.CV	2025-06-05
742	A VLM-based Method for Visual Anomaly Detection in Robotic Scientific Laboratories Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: It has become a key factor in ensuring the stability and safety of experimental processes. To address this challenge, this paper proposes a VLM-based visual reasoning approach that supports different levels of supervision through four progressively informative prompt configurations.	SHIWEI LIN et. al.	arxiv-cs.CV	2025-06-04
743	Distance-based Change Point Detection for Novelty Detection in Concept-agnostic Continual Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Collin Coil; Kamil Faber; Bartlomiej Sniezynski; Roberto Corizzo;	Journal of Intelligent Information Systems	2025-06-03
744	Unmanned Aerial Vehicle Anomaly Detection Based on Causality-Enhanced Graph Neural Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the widespread application of unmanned aerial vehicles (UAVs), the safety detection system of UAVs has created an urgent need for anomaly detection technology. As a direct …	Chen Feng; Jun Fan; Zhiliang Liu; Guang Jin; Siya Chen;	Drones	2025-06-03
745	Investigating Mask-aware Prototype Learning for Tabular Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To tackle the problem, we incorporate mask modeling and prototype learning into tabular anomaly detection.	Ruiying Lu; Jinhan Liu; Chuan Du; Dandan Guo;	arxiv-cs.LG	2025-06-03
746	Anomaly Detection in Network Traffic Via Cross-Domain Federated Graph Representation Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the growing complexity and frequency of network threats, anomaly detection in network traffic has become a vital task for ensuring cybersecurity. Traditional detection …	Yanli Zhao; Zongduo Liu; Junjie Pang;	Applied Sciences	2025-06-02
747	ALAD: A New Unsupervised Time Series Anomaly Detection Paradigm Based on Activation Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Time series anomaly detection has been received growing interest in industrial and academic communities due to its substantial theoretical value and practical significance in …	Fengqian Ding; Bo Li; Xianye Ben; Jia Zhao; Hongchao Zhou;	IEEE Transactions on Big Data	2025-06-01
748	A Novel Transformer Network for Anomaly Detection of Wind Turbine IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Lifeng Cheng; Bohua Chen; Ling Xiang; Aijun Hu; Xinghua Yuan;	Measurement	2025-06-01
749	Hierarchical Temporal Sequence Segmentation for Weakly Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Nuku Atta Kordzo Abiew; L. Gao; Qirong Mao;	Expert Syst. Appl.	2025-06-01
750	Graph Neural Networks with Scattering Transform for Network Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Abdeljalil Zoubir; Badr Missaoui;	Eng. Appl. Artif. Intell.	2025-06-01
751	Hyperparameter Optimization in Unsupervised Anomaly Detection for Mineral Prospectivity Mapping Related Papers Related Patents Related Grants Related Venues Related Experts View Save	SEYYED ATAOLLAH AGHA SEYYED MIRZABOZORG et. al.	Ore Geology Reviews	2025-06-01
752	Anomaly Detection Via Semantically Conjugate View Learning on Industrial Temporal Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection based on knowledge discovery from the industrial temporal data via graph neural networks (GNNs) has been extensively prevailing over the past decade. So far, …	Kai Wang; Shuaiyi Lyu; Bailing Wang; Yongzheng Zhang;	IEEE Internet of Things Journal	2025-06-01
753	Water Quality Anomaly Detection: An Improved Empirical Wavelet Transform Method Related Papers Related Patents Related Grants Related Venues Related Experts View Save	YONG ZHANG et. al.	Water Resources	2025-06-01
754	SVM Algorithm-based Anomaly Detection in Network Logs and Firewall Logs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The purpose of many advanced forms of cyberattack is to deceive the monitors, and as a result, these attacks often involve several kinds, levels, and stages. Existing anomaly …	JOHN BENITO JESUDASAN PETER et. al.	Indonesian Journal of Electrical Engineering and Computer …	2025-06-01
755	Memory Association Guided Unsupervised Anomaly Detection with Adaptive 3D Attention Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Xu Liu; Chunlei Wu; Huan Zhang; Leiquan Wang;	Inf. Fusion	2025-06-01
756	DGAN: Flight Data Anomaly Detection Based on Dual-View Graph Attention Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: A large number of flight data is collected by various sensors during flight, including altitude, speed, pitch, etc. Flight unsafe events, such as hard landings, can be reflected …	WENLONG YAN et. al.	IEEE Sensors Journal	2025-06-01
757	Real-Time Anomaly Detection for Large-Scale Network Devices Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the booming of large-scale network devices, anomaly detection on multivariate time series (MTS), such as a combination of CPU utilization, average response time, and network …	Lei Tao; Shenglin Zhang; Junhua Kuang; Xiao-Wei Guo; Canqun Yang;	IEEE Transactions on Networking	2025-06-01
758	Graph Evidential Learning for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, relying solely on reconstruction error for anomaly detection has limitations, as it increases the sensitivity to noise and overfitting. To address these issues, we propose Graph Evidential Learning (GEL), a probabilistic framework that redefines the reconstruction process through evidential learning.	CHUNYU WEI et. al.	arxiv-cs.LG	2025-05-31
759	Bridging 3D Anomaly Localization and Repair Via High-Quality Continuous Geometric Representation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce Pose-Aware Signed Distance Field (PASDF), a novel framework that integrates 3D anomaly detection and repair by learning a continuous, pose-invariant shape representation.	BOZHONG ZHENG et. al.	arxiv-cs.CV	2025-05-30
760	An Unsupervised Anomaly Detection Method for Nuclear Reactor Coolant Pumps Based on Kernel Self-Organizing Map and Bayesian Posterior Inference Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Effectively monitoring the operational status of reactor coolant pumps (RCPs) is crucial for enhancing the safety and stability of nuclear power operations. To address the …	Lin Wang; Shuqiao Zhou; Tianhao Zhang; Chao Guo; Xiaojin Huang;	Energies	2025-05-30
761	QEA-FAD: Quantum Enhanced Autoencoders for Anomaly Detection in Finance and Healthcare Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Quantum Auto-Encoders (QAEs) represent a transformative approach to anomaly detection, leveraging quantum computational power to address challenges in domains such as healthcare …	Sourodeep Kundu; Deepti Mishra; N. Tarasia; R. K. Lenka; R. Barik;	2025 International Conference on Networks and Cryptology …	2025-05-29
762	Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Unsupervised graph anomaly detection aims at identifying rare patterns that deviate from the majority in a graph without the aid of labels, which is important for a variety of …	YUANCHEN BEI et. al.	IEEE transactions on neural networks and learning systems	2025-05-29
763	AD-GAM: Anomaly Detection in IoT Using Generative AI Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Y. Siwakoti; Danda B. Rawat; Sooie-Hoe Loke;	Artificial Intelligence and Machine Learning for …	2025-05-28
764	Domain Adaptation of Attention Heads for Zero-shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing ZSAD research has shown limitations by either not considering domain adaptation of general-purpose backbone models to anomaly detection domains or by implementing only partial adaptation to some model components. In this paper, we propose HeadCLIP to overcome these limitations by effectively adapting both text and image encoders to the domain.	Kiyoon Jeong; Jaehyuk Heo; Junyeong Son; Pilsung Kang;	arxiv-cs.CV	2025-05-28
765	OmniAD: Detect and Understand Industrial Anomaly Via Multimodal Reasoning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: While anomaly detection has made significant progress, generating detailed analyses that incorporate industrial knowledge remains a challenge. To address this gap, we introduce OmniAD, a novel framework that unifies anomaly detection and understanding for fine-grained analysis.	Shifang Zhao; Yiheng Lin; Lu Han; Yao Zhao; Yunchao Wei;	arxiv-cs.CV	2025-05-28
766	Frequency Self-Adaptation Graph Neural Network for Unsupervised Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	MING GU et. al.	Neural networks : the official journal of the International …	2025-05-27
767	Is Hyperbolic Space All You Need for Medical Anomaly Detection? Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Traditional methods extract features from different layers of pre-trained networks in Euclidean space; however, Euclidean representations fail to effectively capture the hierarchical relationships within these features, leading to suboptimal anomaly detection performance. We propose a novel yet simple approach that projects feature representations into hyperbolic space, aggregates them based on confidence levels, and classifies samples as healthy or anomalous.	ALVARO GONZALEZ-JIMENEZ et. al.	arxiv-cs.CV	2025-05-27
768	SAFEL-IoT: Secure Adaptive Federated Learning with Explainability for Anomaly Detection in 6G-Enabled Smart Industry 5.0 IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The rise of 6G-enabled smart industries necessitates secure, adaptive, and interpretable anomaly detection frameworks capable of operating under dynamic, adversarial, and …	Mohammed Naif Alatawi;	Electronics	2025-05-26
769	An Unsupervised Anomaly Detection Method for Railway Fasteners Based on Knowledge-Distilled Generative Adversarial Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The integrity and stability of railway fasteners are of vital importance to railway safety. To address the challenges of limited anomaly samples, irregular defect geometries, and …	Hongyang Chen; Zhiwei Li; Xinjie Xiao;	Applied Sciences	2025-05-24
770	Validation of A Trained AI Imaging Model for Detecting Diabetic Foot Deformities Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Diabetes is a leading cause of morbidity and mortality, contributing to complications such as cardiovascular disease, kidney failure and lower-limb amputations. Diabetic foot …	Kher Li Teoh; Khare Shubham Hari; Li Lian Ng; Zhiwen Joseph Lo;	International wound journal	2025-05-24
771	Center-aware Residual Anomaly Synthesis for Multi-class Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: Furthermore, the intra-class overlap between normal and abnormal samples, particularly in synthesis-based methods, cannot be ignored and may lead to over-detection. To tackle these issues, we propose a novel Center-aware Residual Anomaly Synthesis (CRAS) method for multi-class anomaly detection.	QIYU CHEN et. al.	arxiv-cs.CV	2025-05-23
772	AI-Enhanced Network Forensic Techniques for Cybercrime Investigation Using The Gray Wolf Adaptive Forensic Anomaly Detection Algorithm (GADFADA) Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The growth of cybercrime indicates a need for advancing forensic techniques to improve detection and prevention capabilities. This paper describes an AI-enhanced Network Forensics …	B. Abisha; V. S. Kumari; Arthi K; K. Durgadevi; Suresh Kumar V;	2025 6th International Conference for Emerging Technology …	2025-05-23
773	Center-Aware Residual Anomaly Synthesis for Multiclass Industrial Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection plays a vital role in the inspection of industrial images. Most existing methods require separate models for each category, resulting in multiplied deployment …	QIYU CHEN et. al.	IEEE Transactions on Industrial Informatics	2025-05-23
774	A Hybrid Deep Learning Approach for Detecting Anomalies in Real-Time Data Streams Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: A crucial problem in many fields, such as cyber-security, financial fraud detection, industrial monitoring, and healthcare, is anomaly identification in real-time data streams. …	Aditya Mohan Mishra; Daksh Yadav; Ananmaya Shakya; Vagh Jayesh; Er. Neetu Bala;	2025 6th International Conference for Emerging Technology …	2025-05-23
775	Anomaly Detection in Smart Grid Load Profiles Via Variational Autoencoders Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Xiaolin Dai;	2025 2nd International Symposium on New Energy Technologies …	2025-05-23
776	Evaluation of Anomaly Detection and Adversarial Attacks in The IEEE 9-Bus System Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: This study focuses on anomaly detection and the impact of adversarial attacks in microgrids, which are critical components of modern power systems. The performance of a Multilayer …	Emrecan Bıngöl; M. S. Ayas; İsmail Hakkı Altaş;	2025 7th International Congress on Human-Computer …	2025-05-23
777	Deep Anomaly Detection on Attributed Networks By Graph Update Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yifan Li; Jiayin Li; Ximeng Liu; Li Xu;	Computing	2025-05-22
778	SD-MAD: Sign-Driven Few-shot Multi-Anomaly Detection in Medical Images Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Thus, in this paper, we propose a framework tailored for few-shot medical anomaly detection in the scenario where the identification of multiple anomaly categories is required.	KAIYU GUO et. al.	arxiv-cs.CV	2025-05-22
779	CAA-RF: An Anomaly Detection Algorithm for Computing Power Blockchain Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: As a distributed communication and storage system, blockchain forms a Computing Power Blockchain Network (CPBN) by integrating computing nodes and network resources. However, its …	Shifeng Jia; Yating Zhao; Yang Zhang; Bin Jia; Wenjuan Lian;	Applied Sciences	2025-05-22
780	Nanotechnology-Enhanced Imaging: Advancing Precision in Fetal Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Biswajeet Acharya; A. Behera; Prafulla Kumar Sahu; Suchismeeta Behera; B. Prajapati;	Biomedical Materials & Devices	2025-05-22
781	Interpretable Anomaly Detection in Encrypted Traffic Using SHAP with Machine Learning Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This study proposes a model-agnostic framework that integrates multiple machine learning classifiers, with SHapley Additive exPlanations SHAP to ensure post-hoc model interpretability.	Kalindi Singh; Aayush Kashyap; Aswani Kumar Cherukuri;	arxiv-cs.CR	2025-05-22
782	Learning to Detect Industrial Time-Series Anomalies From Imputation Consistency With Sparse Observations Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Time-series anomaly detection plays an important role in ensuring industrial safety. Currently, many anomaly detection methods mainly target complete time series and ignore the …	Zhen Zhang; Yongming Han; Zhiqiang Geng;	IEEE transactions on neural networks and learning systems	2025-05-21
783	Optical Fiber Anomaly Detection Through SRS-induced Spectral Tilt in C+L-band Transmission Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Fiber-optic communication systems serve as the backbone of modern data communication networks, with increasing demands on their reliability and robustness in various emerging …	ZIHAO CUI et. al.	Journal of Optical Communications and Networking	2025-05-20
784	GCAFlow: Multi-Scale Flow-Based Model with Global Context-Aware Channel Attention for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, most of the flow-based methods emphasize spatial information while neglecting the critical role of channel-wise features. To address this limitation, we propose GCAFlow, a novel flow-based model enhanced with a global context-aware channel attention mechanism.	Lin Liao; Congde Lu; Yujie Gao; Hao Yu; Biao Cai;	Sensors (Basel, Switzerland)	2025-05-20
785	Anomaly Detection Based Capsnet for Malicious Url Detection System Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Rakan Alsowail;	Wirel. Networks	2025-05-20
786	Multi-Domain Indoor Dataset for Visual Place Recognition and Anomaly Detection By Mobile Robots Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This article presents a freely available dataset for research on place recognition and presents an example application in the field of anomaly detection.	Piotr Wozniak; Tomasz Krzeszowski; Bogdan Kwolek;	Scientific data	2025-05-19
787	Structure-based Anomaly Detection and Clustering Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This thesis proposes new unsupervised methods for anomaly detection in both structured and streaming data settings.	Filippo Leveni;	arxiv-cs.LG	2025-05-19
788	UMGAD: Unsupervised Multiplex Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: (2) In unsupervised scenarios, selecting appropriate anomaly score thresholds remains a significant challenge for accurate anomaly detection. To address the above challenges, we propose a novel Unsupervised Multiplex Graph Anomaly Detection method, named UMGAD.	XIANG LI et. al.	icde	2025-05-19
789	Bridging The Gap: LLM-Powered Transfer Learning for Log Anomaly Detection in New Software Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Cross-system log anomaly detection methods attempt to transfer knowledge from mature systems to new ones but often struggle with syntax differences and system-specific knowledge, which hinders their effectiveness. To address these issues, this paper proposes LogSynergy, a novel transfer learning-based log anomaly detection framework.	YICHENG SUI et. al.	icde	2025-05-19
790	A Review of Anomaly Detection in Spacecraft Telemetry Data IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Telemetry data play a pivotal role in ensuring the success of spacecraft missions and safeguarding the integrity of spacecraft systems. Therefore, the timely detection and …	A. Fejjari; Alexis Delavault; R. Camilleri; G. Valentino;	Applied Sciences	2025-05-19
791	AI for Microservice Monitoring & Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Santhosh Podduturi;	International Conference on Computer Science, Artificial …	2025-05-18
792	Enhancing Network Anomaly Detection with Quantum GANs and Successive Data Injection for Multivariate Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce a quantum generative adversarial network (QGAN) architecture for multivariate time-series anomaly detection that leverages variational quantum circuits (VQCs) in combination with a time-window shifting technique, data re-uploading, and successive data injection (SuDaI).	Wajdi Hammami; Soumaya Cherkaoui; Shengrui Wang;	arxiv-cs.LG	2025-05-16
793	Development of An Integrated Approach to Detecting Anomalies in Multidimensional Data Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The paper analyzes the impact of anomalous data on analytical models in high-dimensional and heterogeneous datasets. It investigates the use of metrics such as accuracy, …	Youry Chechikov; Vitaly Sekretarev;	Computer Applications for Management and Sustainable …	2025-05-16
794	Anomaly Based Intrusion Detection to Enhance IoT Devices Security Using LSTM and Radial Basis Function Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The growing prevalence of IoT devices has rendered their security a paramount issue. Intrusion detection is essential for protecting IoT systems from potential attackers. …	G. V. L. NARAYANA et. al.	2025 3rd International Conference on Data Science and …	2025-05-16
795	Hashing for Structure-based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: In this work, we employ Locality Sensitive Hashing to avoid explicit computation of distances in high dimensions and thus improve Anomaly Detection efficiency.	Filippo Leveni; Luca Magri; Cesare Alippi; Giacomo Boracchi;	arxiv-cs.LG	2025-05-16
796	Cluster-LLM: Adaptive Real-Time Time-Series Anomaly Detection Using LLMs Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Time-series anomaly detection plays a vital role in industrial monitoring, finance, and cybersecurity. However, existing methods often suffer from limited labeled data, poor …	BIN ZHU et. al.	2025 IEEE International Annual Conference on Complex …	2025-05-16
797	A Generalized Non-Convex Surrogated Framework for Anomaly Detection on Blurred Hyperspectral Images Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To this end, this paper proposes a generalized non-convex surrogated tensor framework that is able to perform anomaly detection robustly to blurring effects on hyperspectral images.	Yinjian Wang; Wei Li; Yuanyuan Gui; Haijun Xie; Lianbo Zhang;	IEEE transactions on image processing : a publication of …	2025-05-16
798	Research on Anomaly Detection Algorithm for Marine Vessel Battery Cells Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Jianshe Liu; Jing Chen; Yuchong Zhao;	2025 IEEE 8th International Electrical and Energy …	2025-05-16
799	PIF: Anomaly Detection Via Preference Embedding Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Specifically, we propose to embed the data in a high dimensional space where an efficient tree-based method, PI-Forest, is employed to compute an anomaly score.	Filippo Leveni; Luca Magri; Giacomo Boracchi; Cesare Alippi;	arxiv-cs.LG	2025-05-15
800	Innovative Approaches to Traffic Anomaly Detection and Classification Using AI Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Video anomaly detection plays a crucial role in intelligent transportation systems by enhancing urban mobility and safety. This review provides a comprehensive analysis of recent …	Borja Pérez; Mario Resino; Teresa Seco; Fernando García; Abdulla Al-Kaff;	Applied Sciences	2025-05-15
801	Device Identification and Anomaly Detection in IoT Environments IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: As the Internet of Things (IoT) landscape continues to expand, a diverse range of devices with various functionalities is being integrated into the IoT ecosystem. When traditional …	MAHDI RABBANI et. al.	IEEE Internet of Things Journal	2025-05-15
802	Anomaly Detection in ELI-NP Front-End Laser Energy Data Using An Optimized Moving Average Method Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection in time-series data is critical for ensuring stability in high-power laser systems, where deviations can indicate potential failures. This study optimizes a …	T. Imran;	Romanian Journal of Physics	2025-05-15
803	Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: In the final stage, we propose a weakly-supervised anomaly detection method to train a more powerful model with generated anomalies.	Guan Gui; Bin-Bin Gao; Jun Liu; Chengjie Wang; Yunsheng Wu;	arxiv-cs.CV	2025-05-14
804	Learning to Detect Multi-class Anomalies with Just One Normal Image Prompt IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: To enable reconstruction models enjoying high efficiency while enhancing their generalization for unified anomaly detection, we propose a simple yet effective method that reconstructs normal features and restores anomaly features with just One Normal Image Prompt (OneNIP).	Bin-Bin Gao;	arxiv-cs.CV	2025-05-14
805	Deep Support Vector Data Description of Anomaly Detection with Positive Class Edge Outlier Exposure and Maximum Double Hypersphere Interval Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The existing deep support vector data description (DSVDD) models for anomaly detection still have room for improvement. These models cannot guarantee that the features of abnormal …	GUOWEI YANG et. al.	Other Conferences	2025-05-14
806	Online Isolation Forest Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: We propose Online-iForest, a novel method explicitly designed for streaming conditions that seamlessly tracks the data generating process as it evolves over time.	Filippo Leveni; Guilherme Weigert Cassales; Bernhard Pfahringer; Albert Bifet; Giacomo Boracchi;	arxiv-cs.LG	2025-05-14
807	An Intelligent Construction Equipment Abnormality Online Detection Method Based on Image Recognition Technology Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Conventional intelligent construction equipment anomaly detection is based on the extraction and fusion of anomalous feature signals, which does not take into account the …	Siming Wu;	Other Conferences	2025-05-14
808	Anomaly Detection in Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: -In Network Security is a major challenge in the digital world. Intrusion is common in many applications and intruders are sophisticated enough to change their attack pattern very …	Ravi Kumar D,;	International Scientific Journal of Engineering and …	2025-05-13
809	Cross-Domain Graph Anomaly Detection Via Graph Transfer and Graph Decouple Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Cross‐domain graph anomaly detection (CD‐GAD) is a promising task that leverages knowledge from a labelled source graph to guide anomaly detection on an unlabelled target graph. …	CHANGQIN HUANG et. al.	CAAI Trans. Intell. Technol.	2025-05-13
810	Explainable Anomaly Detection in Network Traffic Using LLM Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Network anomaly detection is essential for modern cybersecurity, yet existing systems often generate numerous alerts without clear explanations, leading to inefficiencies and high …	Kamil Jerábek; Josef Koumar; Jiří Setinský; Jaroslav Pesek;	NOMS 2025-2025 IEEE Network Operations and Management …	2025-05-12
811	EAGLE: Contrastive Learning for Efficient Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, existing methods are lack of efficiency that is definitely necessary for embedded devices. Towards this end, we propose an Efficient Anomaly detection model on heterogeneous Graphs via contrastive LEarning (EAGLE) by contrasting abnormal nodes with normal ones in terms of their distances to the local context.	Jing Ren; Mingliang Hou; Zhixuan Liu; Xiaomei Bai;	arxiv-cs.LG	2025-05-12
812	Inter-patch Spatio-temporal Relation Prediction for Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	HAO SHEN et. al.	Signal, Image and Video Processing	2025-05-12
813	DREAM: Dual FoREcAsting Model for Network Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In this paper, we address the challenge of anomaly detection in multivariate time series data related to environments requiring stringent guarantees, notably in 5G and beyond 5G …	M. BOUDJELLI et. al.	NOMS 2025-2025 IEEE Network Operations and Management …	2025-05-12
814	Boosting Global-Local Feature Matching Via Anomaly Synthesis for Multi-Class Point Cloud Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: However, the feature similarity between normal and anomalous points from different class data leads to the feature confusion problem, which greatly hinders the performance of multi-class methods. Therefore, we introduce a multi-class point cloud anomaly detection method, named GLFM, leveraging global-local feature matching to progressively separate data that are prone to confusion across multiple classes.	Yuqi Cheng; Yunkang Cao; Dongfang Wang; Weiming Shen; Wenlong Li;	arxiv-cs.CV	2025-05-12
815	Polynomial Interpolation-based Anomaly Detection in Injection Pumps Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Water flooding is a crucial method in current oilfield development, and real-time monitoring of the water injection pump system is essential for timely anomaly detection, …	Mei Wang;	3rd International Conference on High Performance Computing …	2025-05-09
816	A Scale Adaptation Autoencoder Model for Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The emergence of generative adversarial networks provides a new approach for anomaly detection, which alleviates the shortage of anomaly sample data in anomaly detection scenarios …	QIFAN GUO et. al.	3rd International Conference on High Performance Computing …	2025-05-09
817	Development of Water Quality Analysis for Anomaly Detection and Correlation with Case Studies in Water Supply Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The increasing importance of water quality management in water supply systems requires the development of efficient methodologies for the early detection of water quality …	RAHMANIA HANIFA et. al.	Electronics	2025-05-09
818	Automatic Analysis and Anomaly Detection Technology of Intelligent Operation and Maintenance Log Integrated with Natural Language Processing Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The traditional manual log analysis approach is increasingly inadequate for meeting the demands of efficient and accurate operation and maintenance. To address this challenge, …	Ziyang Meng; Shuai Xu; Han Wang; Yakun Zhang; Zepeng Wen;	Conference on Electronic Information Engineering and Data …	2025-05-09
819	Unsupervised Anomaly Detection for Autonomous Robots Via Mahalanobis SVDD with Audio-IMU Fusion Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: To this end, we explore the use of audio and inertial measurement unit (IMU) sensors to detect underlying anomalies in autonomous mobile robots, such as collisions and internal mechanical faults.	YIZHUO YANG et. al.	arxiv-cs.RO	2025-05-09
820	Diffusion Graph Model for Time Series Anomaly Detection Via Anomaly-aware Graph Sparsification and Augmentation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Unsupervised methods, particularly reconstruction-based methods have become the dominant approach for multivariate time series anomaly detection (TSAD), which distinguish between …	Disen Lan; Guibin Zhang; Rongjin Guo;	Companion Proceedings of the ACM on Web Conference 2025	2025-05-08
821	Research on Anomaly Detection Methods Based on Diffusion Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, we explore the potential of diffusion models for anomaly detection, proposing a novel framework that leverages the strengths of diffusion probabilistic models (DPMs) to effectively identify anomalies in both image and audio data.	Yi Chen;	arxiv-cs.LG	2025-05-08
822	Backdoor Attack Against Log Anomaly Detection Models Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Detecting anomalies in system logs has been an active research topic because of its importance in detecting system faults and novel attacks. Recently, many log anomaly detection …	He Cheng; Depeng Xu; Shuhan Yuan;	Companion Proceedings of the ACM on Web Conference 2025	2025-05-08
823	MSR-GAN: Multi-scales Decomposition Representations for Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Dongwei Xu; Tianhao Xia; Jiaye Hou; Yun Xiang; Qi Xuan;	Applied Intelligence	2025-05-08
824	Research on Semi-supervised Anomaly Detection in Automatic Verification System of Intelligent Watt-hour Meter Based on Direct Push Support Vector Machine Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the continuous advancement of the construction of smart grid, the demand for smart watt-hour meters is growing day by day, and the importance of watt-hour meter verification …	TIANHONG ZHOU et. al.	Other Conferences	2025-05-07
825	ABC-WSVAD: Swarm Optimization for Weakly-Supervised Video Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Nowadays, Video Anomaly Detection (VAD) has undergone a significant transformation due to advancements in Deep Learning (DL) and Computer Vision (CV). VAD holds substantial …	Iman Mostafa; Marwa Gamal; Rehab F. Abdel-Kader; Khaled Abd El Salam;	Inteligencia Artif.	2025-05-07
826	Enhancing Network Security: Robust Anomaly Detection with Ensemble Learning and Explainable AI Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Network security is a critical issue in the digital era, as the complexity and intelligence of cyber threats pose significant risks to people as well as companies. Traditional …	IBRAHIM GAD et. al.	2025 International Conference on Innovation in Artificial …	2025-05-07
827	Real-Time Freeway Traffic Anomalous Event Detection System Via Radar Detector Sensors Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Undetected anomalous incidents on the freeway, such as crashes, can cause increased congestion and secondary crashes. To address this problem, we recently released a real freeway …	AUSTIN COURSEY et. al.	Proceedings of the ACM/IEEE 16th International Conference …	2025-05-06
828	Low-Shot Unsupervised Visual Anomaly Detection Via Sparse Feature Representation IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This article presents a novel sparse feature representation anomaly detection (SFRAD) framework, which formulates the anomaly detection as a sparse feature representation problem; and notably proposes an anomaly score by orthogonal matching pursuit (ASOMP) as a novel detection metric.	FANGHUI ZHANG et. al.	IEEE transactions on neural networks and learning systems	2025-05-06
829	CXR-AD: Component X-ray Image Dataset for Industrial Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We systematically analyze the dataset characteristics and identify three major technical challenges: (1) strong coupling between complex internal structures and defect regions, (2) inherent low contrast and high noise interference in X-ray imaging, and (3) significant variations in defect scales and morphologies.	HAOYU BAI et. al.	arxiv-cs.CV	2025-05-06
830	Federated Graph Anomaly Detection Via Contrastive Self-Supervised Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Consequently, naively applying federated graph learning directly to anomaly detection tasks in distributed environments may lead to suboptimal performance results. We propose a federated graph anomaly detection framework via contrastive self-supervised learning (CSSL) [federated CSSL anomaly detection framework (FedCAD)] to address these challenges.	XIANGJIE KONG et. al.	IEEE transactions on neural networks and learning systems	2025-05-06
831	Deep Anomaly Detection with Partition Contrastive Learning for Tabular Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yizhou Li; Yijie Wang; Hongzuo Xu; Bin Li; Xiaohui Zhou;	Data Mining and Knowledge Discovery	2025-05-06
832	Efficient Access Control for Video Anomaly Detection Using ABE-Based User-Level Revocation with Ciphertext and Index Updates Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the widespread deployment of video surveillance systems, effective access control is essential to enhance the accuracy and security of video anomaly detection. This paper …	Lu Jiang; Jielu Yan; Weizhi Xian; Xuekai Wei; Xiaofeng Liao;	Applied Sciences	2025-05-05
833	CD-SEM Anomaly Detection Through Machine Learning and Generative AI Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In a complex semiconductor manufacturing environment, critical dimension scanning electron microscope (CD-SEM) images are captured at metrology step to monitor structural …	SUSAN SUN et. al.	2025 36th Annual SEMI Advanced Semiconductor Manufacturing …	2025-05-05
834	Detect, Classify, Act: Categorizing Industrial Anomalies with Multi-Modal Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: However, anomaly classification-distinguishing different types of anomalies-remains largely unexplored despite its critical importance in real-world inspection tasks. To address this gap, we propose VELM, a novel LLM-based pipeline for anomaly classification.	Sassan Mokhtar; Arian Mousakhan; Silvio Galesso; Jawad Tayyub; Thomas Brox;	arxiv-cs.CV	2025-05-05
835	Robustness of Unsupervised Methods for Image Surface-anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Jakob Bozic; Matic Fucka; Vitjan Zavrtanik; D. Skočaj;	Pattern Anal. Appl.	2025-05-03
836	AD-NEv: A Scalable Multilevel Neuroevolution Framework for Multivariate Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we propose anomaly detection neuroevolution (AD-NEv)-a scalable multilevel optimized neuroevolution framework for multivariate time-series anomaly detection.	Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo;	IEEE transactions on neural networks and learning systems	2025-05-02
837	A Deep Learning Approach for Anomaly Detection in X-ray Images of Paintings Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The intersection of technological advancements and cultural heritage studies has intensified the exploration of historical treasures, captivating historians and enthusiasts alike. …	Anzhelika Mezina; Radim Burget; Marek Kotrlý;	npj Heritage Science	2025-05-02
838	Adaptive Memory Broad Learning System for Unsupervised Time Series Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this study, a novel algorithm called adaptive memory broad learning system (AdaMemBLS) is proposed for time series anomaly detection.	Zhijie Zhong; Zhiwen Yu; Ziwei Fan; C L Philip Chen; Kaixiang Yang;	IEEE transactions on neural networks and learning systems	2025-05-02
839	UltraADV: An Unsupervised Deep Learning Lightweight Framework for Anomaly Detection in V2X Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Designing anomaly detection systems for vehicle-to-everything (V2X) is a challenge. Deep learning has shown strong advantages in anomaly detection. However, labeling anomalies is …	WEIXIAN HUANG et. al.	IEEE Internet of Things Journal	2025-05-01
840	Multivariate Time-Series Anomaly Detection Based on Dynamic Graph Neural Networks and Self-Distillation in Industrial Internet of Things Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Time-series anomaly detection is critical to securing the Industrial Internet of Things (IIoT). Although numerous deep learning-based methods have been proposed, these methods …	Mengmeng Zhao; Haipeng Peng; Lixiang Li;	IEEE Internet of Things Journal	2025-05-01
841	NoiseSegAD: Diffusion Model Noise Prediction and Segmentation for Image Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Abstract. Image anomaly detection methods based on autoencoders or generative adversarial networks often reconstruct anomalies due to the generalization capability of neural …	Xin Xie; Xing Zheng; Zhijian Yang; Tijian Cai;	Journal of Electronic Imaging	2025-05-01
842	Spatial Scene Temporal Behavior Framework for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Chaobo Li; Hongjun Li; Guoan Zhang;	Digit. Signal Process.	2025-05-01
843	Threat Detection in Reconfigurable Cyber-Physical Systems Through Spatio-Temporal Anomaly Detection Using Graph Attention Network Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Roberto Canonico; F. Lista; Annalisa Navarro; Giancarlo Sperlí; Andrea Vignali;	Comput. Secur.	2025-05-01
844	A Variational Graph Autoencoder Aided Canonical Correlation Analysis-Based Online Abnormal Patterns Detection Method for Buildings HVAC Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Heating, Ventilation, and Air Conditioning (HVAC) systems have become essential components of contemporary life, extensively employed in commercial and residential settings to …	Xiaogang Pan; Qiao Deng; Yuanyuan Jiao; Zhiwen Chen;	IEEE Transactions on Consumer Electronics	2025-05-01
845	Feature-Adaptive Anomaly Detection Model for Onion Inspection System Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Ziwei Song; Prawit Buayai; Koji Makino; Xiaoyang Mao;	Smart Agricultural Technology	2025-05-01
846	Mixer-transformer: Adaptive Anomaly Detection with Multivariate Time Series Related Papers Related Patents Related Grants Related Venues Related Experts View Save	XING FANG et. al.	J. Netw. Comput. Appl.	2025-05-01
847	Learning Opposite Prompts for Weakly Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Helei Qiu; Biao Hou; Yanyu Cui;	Knowl. Based Syst.	2025-05-01
848	Foreground Natural Anomaly Synthesis for Attention Guided Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Xinyuan Xiang; Meiqin Liu; Senlin Zhang; Ping Wei; Badong Chen;	Neurocomputing	2025-05-01
849	Anomaly-aware Self-supervised Feature Learning for Weakly Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Zhen Yang; Guodong Wang; Yuanfang Guo; Xiuguo Bao; Di-Wei Huang;	Comput. Vis. Image Underst.	2025-05-01
850	A Foundation Model-based Framework for Unsupervised Gaze Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Kritika Johari; Jung-Jae Kim; W. Yow; U-Xuan Tan;	Knowl. Based Syst.	2025-05-01
851	Abductive Learning-guided Uncertainty Modeling for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	QI ZHANG et. al.	Knowl. Based Syst.	2025-05-01
852	Anomaly Detection Using Machine Learning: DBSCAN, Autoencoder and GMM Approaches Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Abstract: This research proposes a novel approach to anomaly detection by combining autoencoders and Gaussian Mixture Models (GMMs). Autoencoders are utilized for dimensionality …	Bhavika Joshi; Prof. Komal Champanerkar;	International Journal for Research in Applied Science and …	2025-04-30
853	Federated Graph Anomaly Detection Via Disentangled Representation Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This partitioning results in incomplete feature aggregation, as the connections between subgraphs are missing, ultimately reducing the performance of anomaly detection models. To overcome these challenges, a federated graph anomaly detection approach based on disentangled representation learning is proposed.	Zhengyang Liu; Hang Yu; Xiangfeng Luo;	www	2025-04-30
854	Learning Multi-view Multi-class Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce a Multi-View Multi-Class Anomaly Detection model (MVMCAD), which integrates information from multiple views to accurately identify anomalies.	Qianzi Yu; Yang Cao; Yu Kang;	arxiv-cs.CV	2025-04-29
855	Unsupervised Surrogate Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we study unsupervised anomaly detection algorithms that learn a neural network representation, i.e. regular patterns of normal data, which anomalies are deviating from.	Simon Klüttermann; Tim Katzke; Emmanuel Müller;	arxiv-cs.LG	2025-04-29
856	Anomaly Detection in Industrial Control Systems Using Machine Learning IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Industrial Control Systems (ICS) are vital components utilized in a number of sectors, such as manufacturing, transportation, and energy. Anomaly detection is crucial to …	P. Kumar; S. Senthil Pandi; L. Bharath Kumar; R. Karthick;	2025 International Conference on Knowledge Engineering and …	2025-04-28
857	A Hybrid and Modular Integration Concept for Anomaly Detection in Industrial Control Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Effective anomaly detection is essential for realizing modern and secure industrial control systems. However, the direct integration of anomaly detection within such a system is …	Christian Goetz; Bernhard G. Humm;	AI	2025-04-27
858	GELog: A GPT-Enhanced Log Representation Method for Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Log anomaly detection is a critical aspect of Artificial Intelligence for IT Operations (AIOps), as it enables the timely identification of system failures, thereby facilitating …	WEN-YUE XU et. al.	2025 IEEE/ACM 33rd International Conference on Program …	2025-04-27
859	Weakly-Supervised Log-Based Anomaly Detection with Inexact Labels Via Multi-Instance Learning IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Log-based anomaly detection is essential for maintaining software availability. However, existing log-based anomaly detection approaches heavily rely on fine-grained exact labels …	MINGHUA HE et. al.	2025 IEEE/ACM 47th International Conference on Software …	2025-04-26
860	Using Graph Neural Networks to Improve Network Traffic Anomaly Detection Performance Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Network traffic anomaly detection is an important part of ensuring the safe and stable operation of the network, but many deep learning-based methods have high computational costs …	Yongsheng Luo;	2025 4th International Conference on Distributed Computing …	2025-04-25
861	Anomaly Detection Algorithm for Multivariate Complex Data Based on Deep Neural Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The conventional data anomaly detection structure is mostly single target execution, and the detection efficiency is relatively low, resulting in an increase in the final false …	GUANGZHI DENG et. al.	2025 4th International Conference on Artificial …	2025-04-25
862	Anomaly Detection Algorithm for Big Data Based on Isolation Forest Algorithm Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the advent of the big data era, anomaly detection becomes increasingly crucial for ensuring the security and reliability of systems. This paper investigates large-scale …	Min He; Xiangfei Chen;	Journal of Computational Methods in Sciences and Engineering	2025-04-25
863	Responsible Workload Sequence Anomaly Detection with Bi-View Feature Fusion Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Chunhong Liu; Dehao Wang; Li Duan; Kun Wang; Junna Zhang;	J. Netw. Syst. Manag.	2025-04-25
864	Anomaly Detection and Optimization Strategy of Power Communication Network Service Quality Based on Machine Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The stability of power communication network is very important in modern power system. However, with the increase of network size and complexity, the detection and optimization of …	Shiliang Wang; Yanxia Ji; Miaomiao Gao; Quanwu Ma; Jiaping Han;	2025 5th Asia-Pacific Conference on Communications …	2025-04-23
865	Toward A Robust Approach to Multivariate Time Series Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection is essential in the semiconductor industry to ensure yield and minimize costs. It becomes particularly critical in high-volume manufacturing (HVM), where …	Jungwook Shon; Simon S. Woo;	Advanced Lithography	2025-04-23
866	Distributed System Log Anomaly Detection Method Based on LSTM Networks and Process State Inspection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Runtime anomaly detection in software plays a critically important role in the management of many large‐scale distributed software systems. Among numerous anomaly detection …	Jinyong Wang; Jiaxuan Hu; Pengda Li;	Quality and Reliability Engineering International	2025-04-23
867	Explainable Unsupervised Anomaly Detection with Random Forest Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We describe the use of an unsupervised Random Forest for similarity learning and improved unsupervised anomaly detection.	Joshua S. Harvey; Joshua Rosaler; Mingshu Li; Dhruv Desai; Dhagash Mehta;	arxiv-stat.ML	2025-04-22
868	Bayesian Autoencoder for Medical Anomaly Detection: Uncertainty-Aware Approach for Brain 2 MRI Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces a Bayesian Variational Autoencoder (VAE) equipped with multi-head attention mechanisms for detecting anomalies in brain magnetic resonance imaging (MRI).	Dip Roy;	arxiv-cs.LG	2025-04-21
869	SADCNN: Supervised Anomaly Detection Based on Convolutional Neural Network Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Maryam Hatami; Hossein Gharaee Garakani; N. Mohammadzadeh;	Inf. Secur. J. A Glob. Perspect.	2025-04-21
870	Dual-Branch Cross-Fusion Normalizing Flow for RGB-D Track Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we aim to exploit the fusion strategy for dual-branch normalizing flow with multi-modal inputs to be applied in the field of track detection.	Xiaorong Gao; Pengxu Wen; Jinlong Li; Lin Luo;	Sensors (Basel, Switzerland)	2025-04-21
871	Research on Abnormal Data Detection in Distribution Networks Using A Parallel Network Integrating GraphSAGE and CNN-GRU Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: As distribution networks advance toward digitalization and intelligence, data quality has become a critical factor for ensuring their safe and stable operation. To address the …	Jilong Zhang; Xiaoli Yao; Fang Niu; Ruoyu Zhao;	Other Conferences	2025-04-18
872	Enhancing Pothole Detection and Characterization: Integrated Segmentation and Depth Estimation in Road Anomaly Systems Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we leverage transfer learning by adopting a pre-trained YOLOv8-seg model for the automatic characterization of potholes using digital images captured from a dashboard-mounted camera.	Uthman Baroudi; Alala BaHamid; Yasser Elalfy; Ziad Al Alami;	arxiv-cs.CV	2025-04-18
873	Quorum: Zero-Training Unsupervised Anomaly Detection Using Quantum Autoencoders Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: The challenge is even greater for anomaly detection, where unsupervised learning methods are essential to ensure practical applicability. To address these issues, we propose Quorum, the first quantum anomaly detection framework designed for unsupervised learning that operates without requiring any training.	Jason Zev Ludmir; Sophia Rebello; Jacob Ruiz; Tirthak Patel;	arxiv-cs.LG	2025-04-17
874	Weakly Supervised Anomaly Detection with Event-level Variables Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: We introduce a new topology for weakly supervised anomaly detection searches,di-object plus~X.	LIAM BRENNAN et. al.	arxiv-hep-ph	2025-04-17
875	AI-Powered Anomaly Detection to Strengthen Internet of Things Security and Forestall Cyber Attacks in Networked Device Environments Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: As millions of devices are linked, the IoT has revolutionized numerous businesses by automating and data-driven decision-making. Due to the proliferation of linked devices, …	S. VARALAKSHMI et. al.	2025 3rd International Conference on Advancement in …	2025-04-17
876	3D-ADCS: Untrained 3D Anomaly Detection for Complex Manufacturing Surfaces Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Surface quality inspection of manufacturing parts through 3D point cloud data has increasingly gained focus in recent years. Accurate 3D anomaly detection on manufacturing parts …	Xuanming Cao; Chengyu Tao; Juan Du;	Journal of Computing and Information Science in Engineering	2025-04-17
877	HSS-IAD: A Heterogeneous Same-Sort Industrial Anomaly Detection Dataset Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: Additionally, the defects do not reflect real-world characteristics. Therefore, we introduce the Heterogeneous Same-Sort Industrial Anomaly Detection (HSS-IAD) dataset, which contains 8,580 images of metallic-like industrial parts and precise anomaly annotations.	QISHAN WANG et. al.	arxiv-cs.CV	2025-04-17
878	LAD-Reasoner: Tiny Multimodal Models Are Good Reasoners for Logical Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We propose a new framework, LAD-Reasoner, a customized tiny multimodal language model built on Qwen2.5-VL 3B.	WEIJIA LI et. al.	arxiv-cs.CV	2025-04-17
879	Enhanced Anomaly Network Intrusion Detection Using An Improved Snow Ablation Optimizer with Dimensionality Reduction and Hybrid Deep Learning Model IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This manuscript proposes an Enhanced Anomaly Intrusion Detection using an Optimization Algorithm with Dimensionality Reduction and Hybrid Model (EAID-OADRHM) technique.	FATIMAH ALHAYAN et. al.	Scientific reports	2025-04-17
880	Reevaluating The Potential of A Vanilla Transformer Encoder for Unsupervised Time Series Anomaly Detection in Sensor Applications Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Unsupervised time series anomaly detection provides practical approaches to addressing the challenges of collecting anomalous data.	Chan Sik Han; HyungWon Kim; Keon Myung Lee;	Sensors (Basel, Switzerland)	2025-04-16
881	Spatio-Temporal Mixed Graph Neural Controlled Differential Equations with Adaptive Connection Sampling for Irregular Multivariate Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces STMG-AD, a spatio-temporal mixed graph neural controlled differential equation method with adaptive connection sampling, designed specifically for anomaly detection in irregular multivariate time series.	X. Jia; W. Peng; C. Shen; B. Zhao; P. Xun;	icassp	2025-04-15
882	Vision-text Enhancement Network For Weakly Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, such solutions ignore the textual information in the dataset and the anomaly event localization. To address these issues, this paper proposes the vision-text enhancement network (VTENet).	Y. CHEN et. al.	icassp	2025-04-15
883	C2AD: Dual Consistency Learning for Zero-Shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Additionally, their representations of anomalies are sensitive to contextual variations, leading to poor localization of unseen abnormalities. Therefore, this paper introduces the Dual Consistency Learning for Zero-Shot Anomaly Detection (C2AD), comprising two components: semantic and contextual consistency.	X. Wang;	icassp	2025-04-15
884	Kernel-Based Anomaly Detection Using Generalized Hyperbolic Processes Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: We present a novel approach to anomaly detection by integrating Generalized Hyperbolic (GH) processes into kernel-based methods.	P. Bourigault; D. P. Mandic;	icassp	2025-04-15
885	Possibility for Proactive Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we present a \textit{proactive} approach for time-series anomaly detection based on a time-series forecasting model specialized for anomaly detection and a data-driven anomaly detection model.	JINSUNG JEON et. al.	arxiv-cs.LG	2025-04-15
886	InstAD: Instance-aware Segmentation Framework for Zero-shot Multi-instance Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we introduce InstAD, a zero-shot multi-instance anomaly detection framework that achieves high accuracy with unaligned multi-instances.	C. -Y. Ho; S. -H. Lai;	icassp	2025-04-15
887	Frequency-enhanced Comprehensive Dependency Attention for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, these approaches often overlook the equally crucial asynchronous inter-variable dependencies, potentially missing anomalous patterns that arise from intricate, temporally offset interactions among variables. Therefore, we propose a novel time series anomaly detection method by perceiving comprehensive intrinsic dependencies of time series data.	H. CHEN et. al.	icassp	2025-04-15
888	A Training-Free Correlation-Weighted Model for Zero-/Few-Shot Industrial Anomaly Detection with Retrieval Augmentation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we introduce a training-free, CLIP-based model that utilizes patch correlations and prototype guidance to enable zero-shot and few-shot anomaly detection.	W. Ran; Z. Yu; S. Xiang; T. Liu; Y. Fu;	icassp	2025-04-15
889	Strengthening Anomaly Awareness Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We present a refined version of the Anomaly Awareness framework for enhancing unsupervised anomaly detection.	Adam Banda; Charanjit K. Khosa; Veronica Sanz;	arxiv-hep-ph	2025-04-15
890	GPT-LAD: Leveraging Large Multimodal Models for Logical Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, no existing methods replicate the way humans set and compare against normality criteria to judge normality. To address this gap, we propose a novel framework that mimics human reasoning by defining normality criteria and leveraging GPT-4V’s advanced logical reasoning capabilities.	Y. An; D. Kang;	icassp	2025-04-15
891	Padnet: A Patch-Based Anomaly Detection Framework for Industrial Pipeline Damage Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper proposes a novel patch-based Anomaly Detection Network (PADNet), that employs deep learning for detecting insulated pipe damages.	E. Alexaki; C. Papaioannidis; V. Mygdalis; I. Pitas;	icassp	2025-04-15
892	SlowFastVAD: Video Anomaly Detection Via Integrating Simple Detector and RAG-Enhanced Vision-Language Model Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, their high computational cost and lack of domain adaptation hinder real-time deployment and reliability. Inspired by dual complementary pathways in human visual perception, we propose SlowFastVAD, a hybrid framework that integrates a fast anomaly detector with a slow anomaly detector (namely a retrieval augmented generation (RAG) enhanced VLM), to address these limitations.	ZONGCAN DING et. al.	arxiv-cs.CV	2025-04-14
893	Adaptive Anomaly Detection in Database Transactions: Bridging Security Gaps with Reinforcement Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection in database transactions is critical for safeguarding sensitive information and ensuring the integrity of operations in industries like finance, healthcare, and …	Clifton Reddy; S. Prabhagaran; Adarsh Vaid;	European Journal of Artificial Intelligence and Machine …	2025-04-14
894	Self-Aware AI-Based Anomaly Detection for AI IoT Enabled Smart Healthcare System Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The Internet of Things (IoT) based smart healthcare systems can significantly enhance the quality of patient care. These systems can enable healthcare providers to monitor patient …	Yusra Shereen; M. F. Shahid; M. Tanveer;	2025 4th International Conference on Computing and …	2025-04-13
895	MADLLM: Multivariate Anomaly Detection Via Pre-trained LLMs Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper introduces MADLLM, a novel multivariate anomaly detection method via pre-trained LLMs.	WEI TAO et. al.	arxiv-cs.CL	2025-04-13
896	T-GAN: Transformer-based Generative Adversarial Network for Network Traffic Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: With the rapid development of network technologies, network traffic anomaly detection has become critical for ensuring information security and network stability. However, …	Weimin Yin; Chao Wang; Yifan Qin;	Proceedings of the 2025 2nd International Conference on …	2025-04-11
897	Anomaly Identification and Prediction Method for Network Timing Data Based on Improved Isolated Forest Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Aiming at the problem of insufficient real-time and poor adaptability to dynamic changes in network timing data anomaly detection, this paper proposes an anomaly identification …	Xianlang Hu; Zhongliang Zhang; Ruini Wang; Chuntian Hu;	2025 IEEE 6th International Seminar on Artificial …	2025-04-11
898	A Survey on Anomaly Detection in IoT Networks: From Classical Methods to AI-Powered Solutions Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: IoT networks enable seamless connectivity but face security challenges due to their scale and complexity. This survey reviews anomaly detection techniques, including machine …	Kumkum Dubey; Isha Batra; Abhishek Bajpai; Arun Malik;	2025 Seventh International Conference on Computational …	2025-04-11
899	Patch Distribution Modeling Framework Adaptive Cosine Estimator (PaDiM-ACE) for Anomaly Detection and Localization in Synthetic Aperture Radar Imagery Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: This work presents a new approach to anomaly detection and localization in synthetic aperture radar imagery (SAR), expanding upon the existing patch distribution modeling framework (PaDiM).	Angelina Ibarra; Joshua Peeples;	arxiv-cs.CV	2025-04-10
900	PatchTrAD: A Patch-Based Transformer Focusing on Patch-Wise Reconstruction Error for Time Series Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we introduce PatchTrAD, a Patch-based Transformer model for time series anomaly detection.	Samy-Melwan Vilhes; Gilles Gasso; Mokhtar Z Alaya;	arxiv-cs.LG	2025-04-10
901	Benchmarking Suite for Synthetic Aperture Radar Imagery Anomaly Detection (SARIAD) Algorithms Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: However, there is no method for developing and benchmarking these methods on SAR imagery. To address this issue, we introduce SAR imagery anomaly detection (SARIAD).	Lucian Chauvina; Somil Guptac; Angelina Ibarrac; Joshua Peeples;	arxiv-cs.CV	2025-04-10
902	Semantic‐consistent Diffusion Model for Unsupervised Traumatic Brain Injury Detection and Segmentation from Computed Tomography Images Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Unsupervised traumatic brain injury (TBI) lesion detection aims to identify and segment abnormal regions, such as cerebral edema and hemorrhages, using only healthy training data. …	Diya Sun; Yuru Pei; Liyi Ying; Tianbing Wang;	Medical Physics	2025-04-09
903	AVadCLIP: Audio-Visual Collaboration for Robust Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: With the increasing adoption of video anomaly detection in intelligent surveillance domains, conventional visual-based detection approaches often struggle with information insufficiency and high false-positive rates in complex environments. To address these limitations, we present a novel weakly supervised framework that leverages audio-visual collaboration for robust video anomaly detection.	PENG WU et. al.	arxiv-cs.CV	2025-04-06
904	AnomalyHybrid: A Domain-agnostic Generative Framework for General Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present AnomalyHybrid, a domain-agnostic framework designed to generate authentic and diverse anomalies simply by combining the reference and target images.	Ying Zhao;	arxiv-cs.CV	2025-04-05
905	Pyramid-based Mamba Multi-class Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce a state space model (SSM)-based Pyramidal Scanning Strategy (PSS) for multi-class anomaly detection and localization–a novel approach designed to address the challenge of small anomaly localization.	Nasar Iqbal; Niki Martinel;	arxiv-cs.CV	2025-04-04
906	Improving Radiologist Detection of Meniscal Abnormality on Undersampled, Deep Learning Reconstructed Knee MRI Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Accurate interpretation of meniscal anomalies on knee MRI is critical for diagnosis and treatment planning, with artificial intelligence emerging as a promising tool to support …	NATALIA KONOVALOVA et. al.	Radiology advances	2025-04-04
907	Localize-diffusion Based Dual-branch Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Jielin Jiang; Xiying Liu; Peiyi Yan; Shun Wei; Yan Cui;	Neural networks : the official journal of the International …	2025-04-03
908	Distributed Log-driven Anomaly Detection System Based on Evolving Decision Making Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: These limitations not only hinder the detection of new threats but also impair overall system performance. To address these challenges, we propose CEDLog, a novel practical framework that integrates Elastic Weight Consolidation (EWC) for continual learning and implements distributed computing for scalable processing by integrating Apache Airflow and Dask.	ZHUORAN TAN et. al.	arxiv-cs.CR	2025-04-03
909	Anomaly Detection in Time Series Data Using Reinforcement Learning, Variational Autoencoder, and Active Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: A novel approach to detecting anomalies in time series data is presented in this paper.	Bahareh Golchin; Banafsheh Rekabdar;	arxiv-cs.LG	2025-04-03
910	CRC-SGAD: Conformal Risk Control for Supervised Graph Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Thus we propose CRC-SGAD, a framework integrating statistical risk control into GAD via two innovations: (1) A Dual-Threshold Conformal Risk Control mechanism that provides theoretically guaranteed bounds for both False Negative Rate (FNR) and False Positive Rate (FPR) through providing prediction sets; (2) A Subgraph-aware Spectral Graph Neural Calibrator (SSGNC) that optimizes node representations through adaptive spectral filtering while reducing the size of prediction sets via hybrid loss optimization.	Songran Bai; Xiaolong Zheng; Daniel Dajun Zeng;	arxiv-cs.LG	2025-04-02
911	Real-Time Anomaly Detection in Industrial IoT: AI-Based Predictive Maintenance Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The increasing adoption of the Industrial Internet of Things (IIoT) has enabled real-time monitoring of industrial systems, yet unexpected failures remain a critical challenge. …	AYUSHI CHOPRA et. al.	2025 12th International Conference on Computing for …	2025-04-02
912	Advanced Techniques for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Abdul Wahid; Praveen Kumar Donta;		2025-04-02
913	CNN-based Anomaly Signal Detection for Telescopes Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly signal detection is particularly crucial in the field of astronomy, especially for monitoring signals from telescopes. With advancements in astronomical observation …	Hongrui Shi;	Other Conferences	2025-04-02
914	3D Vision-based Anomaly Detection in Manufacturing: A Survey IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Surface quality monitoring of manufacturing products is critical for manufacturing industries to ensure product quality and production efficiency. With the rapid development of 3D …	Juan Du; Chengyu Tao; Xuanming Cao; F. Tsung;	Frontiers of Engineering Management	2025-04-02
915	Multimodal Fusion-based Anomaly Detection in The Friction Stir Welding Process Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: As a solid-state joining technology, Friction Stir Welding (FSW) has found widespread application in industries such as aerospace, automotive, and shipbuilding. However, …	GUANHAN LU et. al.	Other Conferences	2025-04-02
916	UniSTAD: An Unified Triple-Tower Student–Teacher Model for Multi-Class Anomaly Detection and Localization Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Despite the rapid advancements in the unsupervised anomaly detection and localization, most existing methods require to train different models for different categories, leading to …	Huan Liu; Jian Sun;	IEEE Transactions on Circuits and Systems for Video …	2025-04-01
917	FLADEN: Federated Learning for Anomaly DEtection in IoT Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Fatma Hendaoui; Rahma Meddeb; Lamia Trabelsi; Ahlem Ferchichi; Rawia Ahmed;	Comput. Secur.	2025-04-01
918	Automatic Threshold Setting for Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Adam Jablonski; Krzysztof Mendrok;	Mechanical Systems and Signal Processing	2025-04-01
919	Conformal Anomaly Detection for Functional Data with Elastic Distance Metrics Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: We present an inductive conformal anomaly detection method based on elastic functional distance metrics.	Jason Adams; Brandon Berman; Joshua Michalenko; J. Derek Tucker;	arxiv-stat.ME	2025-04-01
920	Histogram-based Network Traffic Representation for Anomaly Detection Through PCA Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Sara Baldoni; Federica Battisti;	Comput. Networks	2025-04-01
921	Spectral Jump Anomaly Detection: Temperature-compensated Algorithm for Structural Damage Detection Using Vibration Data Related Papers Related Patents Related Grants Related Venues Related Experts View Save	G. Mariniello; Tommaso Pastore; Domenico Asprone;	Automation in Construction	2025-04-01
922	Online Ensemble Learning-based Anomaly Detection for IoT Systems IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Yafeng Wu; Lan Liu; Yongjie Yu; Guiming Chen; Junhan Hu;	Appl. Soft Comput.	2025-04-01
923	Anomaly Detection Through Deep Feature Extraction for Automatic Defect Detection in Quadratic Frequency Modulated Thermal Wave Imaging Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Naga Prasanthi Yerneni; V. Ghali; M. Swapna; G. T. Vesala;	Russian Journal of Nondestructive Testing	2025-04-01
924	Contrastive Learning for Anomaly Detection in Hierarchical Subgraph Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Jiayang Wu; Wensheng Gan; Jiahao Zhang; Phillp S. Yu;	Knowl. Based Syst.	2025-04-01
925	Spatiotemporal Transform Network-Based Anomaly Detection and Localization of Distributed Parameter Systems Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Due to complex spatiotemporal couplings, it is difficult to detect and locate spatiotemporal abnormal sources for distributed parameter systems (DPSs) with unknown governing …	Peng Wei; Wenchao Zhu; Yang Yang; Zicheng Fei; Changjun Xie;	IEEE Transactions on Industrial Informatics	2025-04-01
926	Anomaly Detection in Smart Home IoT Systems Using Machine Learning Approaches Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The rise of smart home technology, driven by the Internet of Things (IoT), has introduced unprecedented convenience and control into daily life. However, these interconnected …	Rajesh Rajaan; Loveleen Kumar; Nilam Choudhary; Aakriti Sharma; Mani Butwall;	International Journal of Engineering, Business and …	2025-04-01
927	Wear Anomaly Detection Method of Tunnel Boring Machine Disc Cutters Based on Anomaly-attention Improved Long Short-term Memory Autoencoder Related Papers Related Patents Related Grants Related Venues Related Experts View Save	KAI ZHANG et. al.	Measurement	2025-04-01
928	Radiation Anomaly Detection with Source Identification Capability Using Short-time Fourier Transform Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Radiation anomaly detection has been always a crucial task for homeland security to protect citizens from hazardous radiation exposure. Designing detection methods that achieve …	Assem M. Abdelhakim;	Journal of Instrumentation	2025-04-01
929	Tackling The Anomaly Detection Challenge in Large-scale Wireless Sensor Networks Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: One of the areas of ensuring the security of a wireless sensor network (WSN) is anomaly detection, which identifies deviations from normal behavior. In our paper, we investigate …	T. ZHUKABAYEVA et. al.	International Journal of Electrical and Computer …	2025-04-01
930	Dual Flow Reverse Distillation for Unsupervised Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	XUE-QIN JIANG et. al.	Digit. Signal Process.	2025-04-01
931	OIL-AD: An Anomaly Detection Framework for Decision-making Sequences Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Chen Wang; Sarah M. Erfani; Tansu Alpcan; Christopher Leckie;	Pattern Recognit.	2025-04-01
932	GAL-MAD: Towards Explainable Anomaly Detection in Microservice Applications Using Graph Attention Networks Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: We propose a novel anomaly detection model called Graph Attention and LSTM-based Microservice Anomaly Detection (GAL-MAD), leveraging Graph Attention and Long Short-Term Memory architectures to capture spatial and temporal dependencies in microservices.	Lahiru Akmeemana; Chamodya Attanayake; Husni Faiz; Sandareka Wickramanayake;	arxiv-cs.SE	2025-03-31
933	Evaluating Deep Learning Algorithms for Log-Based Anomaly Detection: Insights from Public and Private Datasets Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection in network logs is crucial for maintaining the security and efficiency of modern IT systems. This paper evaluates several deep learning algorithms, including …	Mukesh Yadav; Dhirendra S. Mishra;	Journal of Information Systems Engineering and Management	2025-03-31
934	Bridging The Gap Between Anomaly Detection and Runtime Verification: H-Classifiers Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Runtime Verification (RV) and Anomaly Detection (AD) are crucial for ensuring the reliability of cyber-physical systems, but existing methods often suffer from high computational …	Hagen Heermann; Christoph Grimm;	2025 Design, Automation & Test in Europe Conference (DATE)	2025-03-31
935	Federated Structured Sparse PCA for Anomaly Detection in IoT Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Although federated learning has gained prominence as a privacy-preserving framework tailored for distributed Internet of Things (IoT) environments, current federated principal component analysis (PCA) methods lack integration of sparsity, a critical feature for robust anomaly detection. To address this limitation, we propose a novel federated structured sparse PCA (FedSSP) approach for anomaly detection in IoT networks.	Chenyi Huang; Xinrong Li; Xianchao Xiu;	arxiv-cs.LG	2025-03-31
936	Anomaly Detection in HR Data Using Variational Autoencoders: A Deep Learning Approach to Fraud Detection and Performance Outliers Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Fraud detection in Human Resource Management is a critical issue because payroll fraud and performance anomalies will lead to loss and inefficiency. Traditional fraud detection …	THIRUSUBRAMANIAN GANESAN et. al.	World Journal of Advanced Engineering Technology and …	2025-03-30
937	Optical Fiber Anomaly Detection Using Channel Power Tilt Through Forward and Inverse Calculation of ISRS Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The proposed low-complexity fiber anomaly detection method, utilizes power tilt comparison from forward and backward ISRS calculation, demonstrating maximum positioning error of …	ZIHAO CUI et. al.	2025 Optical Fiber Communications Conference and Exhibition …	2025-03-30
938	Unsupervised Anomaly Detection in Multivariate Time Series Across Heterogeneous Domains Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: In this paper, we begin by introducing a unifying framework for benchmarking unsupervised anomaly detection (AD) methods, and highlight the problem of shifts in normal behaviors that can occur in practical AIOps scenarios.	Vincent Jacob; Yanlei Diao;	arxiv-cs.LG	2025-03-29
939	Global Temporal Attention-Driven Transformer Model for Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Jie Liu;	2025 5th International Conference on Artificial …	2025-03-28
940	AssistPDA: An Online Video Surveillance Assistant for Video Anomaly Prediction, Detection, and Analysis Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To enhance the ability to model intricate spatiotemporal relationships in anomaly events, we propose a Spatio-Temporal Relation Distillation (STRD) module.	ZHIWEI YANG et. al.	arxiv-cs.CV	2025-03-27
941	Anomaly Detection in Retinal OCT Images With Deep Learning-Based Knowledge Distillation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: The purpose of this study was to develop a robust and general purpose artificial intelligence (AI) system that allows the identification of retinal optical coherence tomography (OCT) volumes with pathomorphological manifestations not present in normal eyes in screening programs and large retrospective studies.	Guilherme Aresta; Teresa Araújo; Ursula Schmidt-Erfurth; Hrvoje Bogunovic;	Translational vision science & technology	2025-03-27
942	Multi-scale Spatiotemporal Normality Learning for Unsupervised Video Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Caitian Liu; Linxiao Gong; Xiong Chen;	Appl. Intell.	2025-03-26
943	Enhancing Anomaly Detection in Structured Data Using Siamese Neural Networks As A Feature Extractor Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection in structured data presents significant challenges, particularly in scenarios with extreme class imbalance. The Siamese Neural Network (SNN) is traditionally …	Elizabeth P. Chou; Bo-Cheng Hsieh;	Mathematics	2025-03-26
944	Sensor Fusion Enhances Anomaly Detection in A Flood Forecasting System Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: To build an Internet of Things (IoT) infrastructure that provides flood susceptibility forecasts for granular geographic levels, an extensive network of IoT weather sensors in …	Andrew Ma; Abhir Karande; Natalie Dahlquist; Fabien Ferrero; N. R. Nguyen;	J. Sens. Actuator Networks	2025-03-25
945	A Lightweight Approach to Comprehensive Fabric Anomaly Detection Modeling Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In order to solve the problem of high computational resource consumption in fabric anomaly detection, we propose a lightweight network, GH-YOLOx, which integrates ghost …	Shuqin Cui; Weihong Liu; Min Li;	Sensors (Basel, Switzerland)	2025-03-25
946	Video Anomaly Detection with Contours – A Study Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: To further reduce the computational complexity of Pose-based Video Anomaly Detection solutions, all methods in this study are based on shallow Neural Networks from the field of Deep Learning, and evaluated on the three most prominent benchmark datasets within Video Anomaly Detection and their human-related counterparts, totaling six datasets.	Mia Siemon; Ivan Nikolov; Thomas B. Moeslund; Kamal Nasrollahi;	arxiv-cs.CV	2025-03-25
947	Ensemble Denoising Autoencoders Based on Broad Learning System for Time-Series Anomaly Detection IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Time-series anomaly detection has gained considerable prominence in numerous practical applications across various domains. Nonetheless, the scarcity of labels leads to the …	Yuanxin Lin; Zhiwen Yu; Kaixiang Yang; C L Philip Chen;	IEEE transactions on neural networks and learning systems	2025-03-24
948	ViCap-AD: Video Caption-based Weakly Supervised Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Junwoo Lim; Juyeob Lee; Hyunji Kim; Eunil Park;	Mach. Vis. Appl.	2025-03-24
949	Anomaly Detection Method Considering PLC Control Logic Structure for ICS Cyber Threat Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection systems are being studied to detect cyberattacks in industrial control systems (ICSs). Existing ICS anomaly detection systems monitor network packets or …	Ju Hyeon Lee; I. Ji; Seungho Jeon; J. Seo;	Applied Sciences	2025-03-23
950	Personalizing Vision-Language Models With Hybrid Prompts for Zero-Shot Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: As an alternative to reference images, this study explores the use of widely available product standards to characterize normal contexts and potential abnormal states. Specifically, this study introduces AnomalyVLM, which leverages generalized pretrained vision-language models (VLMs) to interpret these standards and detect anomalies.	YUNKANG CAO et. al.	IEEE transactions on cybernetics	2025-03-21
951	Secure and Scalable Anomaly Detection in Cloud Environments Using Hidden Markov Models, SMPC, and Decentralized Federated Learning Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Cloud security is under threats of anomalies, which indicate cyber threats. The centralized methods of the traditional system have been struggling with scalability and privacy. …	SWAPNA NARLA et. al.	2025 International Conference on Wireless Communications …	2025-03-20
952	Zero-shot 3D Anomaly Detection Via Online Voter Mechanism Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Wukun Zheng; Xiao Ke; Wenzhong Guo;	Neural networks : the official journal of the International …	2025-03-19
953	Robust Distribution Alignment for Industrial Anomaly Detection Under Distribution Shift Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Existing methods attempt to address domain shifts by training generalizable models but often rely on prior knowledge of target distributions and can hardly generalise to backbones designed for other data modalities. To overcome these limitations, we build upon memory-bank-based anomaly detection methods, optimizing a robust Sinkhorn distance on limited target training data to enhance generalization to unseen target domains.	JINGYI LIAO et. al.	arxiv-cs.CV	2025-03-19
954	Reducing Communication Overhead in Federated Learning for Network Anomaly Detection with Adaptive Client Selection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents an adaptive FL framework combining batch size optimization, client selection, and asynchronous updates for efficient anomaly detection.	William Marfo; Deepak Tosh; Shirley Moore; Joshua Suetterlein; Joseph Manzano;	arxiv-cs.DC	2025-03-19
955	LogLLaMA: Transformer-based Log Anomaly Detection with LLaMA Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose LogLLaMA, a novel framework that leverages LLaMA2.	Zhuoyi Yang; Ian G. Harris;	arxiv-cs.LG	2025-03-18
956	Generative Adversarial Message Passing-based Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	LEILEI MA et. al.	J. King Saud Univ. Comput. Inf. Sci.	2025-03-18
957	EIAD: Explainable Industrial Anomaly Detection Via Multi-Modal Large Language Models Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Furthermore, the application of large multi-modal models in IAD remains in its infancy, facing challenges in balancing question-answering (QA) performance and mask-based grounding capabilities, often owing to overfitting during the fine-tuning process. To address these challenges, we propose a novel approach that introduces a dedicated multi-modal defect localization module to decouple the dialog functionality from the core feature extraction.	Zongyun Zhang; Jiacheng Ruan; Xian Gao; Ting Liu; Yuzhuo Fu;	arxiv-cs.AI	2025-03-18
958	Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: Despite a plethora of anomaly detection models developed over the years, their ability to generalize to unseen anomalies remains an issue, particularly in critical systems. This paper aims to address this challenge by introducing Swift Hydra, a new framework for training an anomaly detection method based on generative AI and reinforcement learning (RL).	NGUYEN HOANG KHOI DO et. al.	iclr	2025-03-17
959	Digital Twin-Based Federated Transfer Learning for Anomaly Detection in Industrial IoT Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection is increasingly becoming crucial for maintaining the safety, reliability, and efficiency of industrial systems. Recently, with the advent of data-driven …	M. Belay; Adil Rasheed; P. S. Rossi;	2025 IEEE Symposium on Computational Intelligence on …	2025-03-17
960	Language-guided Open-world Video Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paradigm necessitates establishing a robust mapping from video and textual definition to anomaly score. Therefore, we propose LaGoVAD (Language-guided Open-world VAD), a model that dynamically adapts anomaly definitions through two regularization strategies: diversifying the relative durations of anomalies via dynamic video synthesis, and enhancing feature robustness through contrastive learning with negative mining.	Zihao Liu; Xiaoyu Wu; Jianqin Wu; Xuxu Wang; Linlin Yang;	arxiv-cs.CV	2025-03-17
961	Adversarially Robust Anomaly Detection Through Spurious Negative Pair Mitigation Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: These pairs introduce noise and misguide the direction of inter-group adversarial perturbations. To overcome the effect of spurious negative pairs, we define opposite pairs and adversarially pull them apart to strengthen inter-group perturbations.	Hossein Mirzaei; Mojtaba Nafez; Jafar Habibi; Mohammad Sabokrou; Mohammad Hossein Rohban;	iclr	2025-03-17
962	One-for-All Few-Shot Anomaly Detection Via Instance-Induced Prompt Learning IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Anomaly detection methods under the ‘one-for-all’ paradigm aim to develop a unified model capable of detecting anomalies across multiple classes.	Wenxi Lv; Qinliang Su; Wenchao Xu;	iclr	2025-03-17
963	AFR-CLIP: Enhancing Zero-Shot Industrial Anomaly Detection with Stateless-to-Stateful Anomaly Feature Rectification Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: However, CLIP’s alignment withobject categories instead of their anomalous states limits its effectivenessfor anomaly detection. To address this limitation, we propose AFR-CLIP, aCLIP-based anomaly feature rectification framework.	JINGYI YUAN et. al.	arxiv-cs.CV	2025-03-17
964	AnoLLM: Large Language Models for Tabular Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: We introduce AnoLLM, a novel framework that leverages large language models (LLMs) for unsupervised tabular anomaly detection.	Che-Ping Tsai; Ganyu Teng; Phillip Wallis; Wei Ding;	iclr	2025-03-17
965	Towards A General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Existing methods require training one specific model for each dataset, which exhibits limited generalization capability across different target datasets, hindering anomaly detection performance in various scenarios with scarce training data. Aiming at this problem, we propose constructing a general time series anomaly detection model, which is pre-trained on extensive multi-domain datasets and can subsequently apply to a multitude of downstream scenarios.	QICHAO SHENTU et. al.	iclr	2025-03-17
966	Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: To bridge the gap, in this work, we present a Unified Benchmark for unsupervised Graph-level OOD and anomaly Detection (UB-GOLD), a comprehensive evaluation framework that unifies GLAD and GLOD under the concept of generalized graph-level OOD detection.	YILI WANG et. al.	iclr	2025-03-17
967	STAGE Framework: A Stock Dynamic Anomaly Detection and Trend Prediction Model Based on Graph Attention Network and Sparse Spatiotemporal Convolutional Network Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: As the financial market becomes increasingly complex, stock prediction and anomaly data detection have emerged as crucial tasks in financial risk management. However, existing …	Ming Shi; Roznim Mohamad Rasli; Shir Li Wang;	PloS one	2025-03-17
968	DRL: Decomposed Representation Learning for Tabular Anomaly Detection IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Most state-of-the-art TAD studies are along the line of reconstruction, which first reconstruct training data and then use reconstruction errors to decide anomalies; however, reconstruction on training data can still hardly distinguish anomalies due to the data entanglement in their representations. To address this problem, in this paper, we propose a novel approach Decomposed Representation Learning (DRL), to re-map data into a tailor-designed constrained space, in order to capture the underlying shared patterns of normal samples and differ anomalous patterns for TAD.	HANGTING YE et. al.	iclr	2025-03-17
969	Generative Inpainting-Based Anomaly Detection for CT Liver Tumor Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: CT is a main modality for imaging liver diseases, valuable in detecting and localizing liver tumors. Traditional anomaly detection methods analyze reconstructed images to identify …	YONGYI SHI et. al.	IEEE transactions on radiation and plasma medical sciences	2025-03-17
970	UCF-Crime-DVS: A Novel Event-Based Dataset for Video Anomaly Detection with Spiking Neural Networks IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: This work explores the potential application of dynamic information from event data in video anomaly detection.	YUANBIN QIAN et. al.	arxiv-cs.CV	2025-03-17
971	A Prediction-Based Anomaly Detection Method for Traffic Flow Data with Multi-Domain Feature Extraction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The core idea of prediction-based anomaly detection is to identify anomalies by constructing a prediction model and comparing predicted and observed values. However, most existing …	XIANGUANG JIA et. al.	Applied Sciences	2025-03-16
972	Robust Isolation Forest Using Soft Sparse Random Projection and Valley Emphasis Method Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Additionally, the challenge of isolating rare and widely distributed anomalies persisted in research focused on improving splits. To address these challenges, we introduce Robust iForest (RiForest).	Hun Kang; Kyoungok Kim;	arxiv-cs.LG	2025-03-15
973	Time-Efficient Video Anomaly Detection With Parallel Computing and Twice-Reconstruction Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: To tackle two prevalent challenges in video anomaly detection, misclassification of abnormal frames as normal and the prolonged runtime of existing methods, this article proposes …	Xiaosha Qi; Xin Chao; Genlin Ji; Le Li;	IEEE Sensors Journal	2025-03-15
974	DATA AUGMENTATION FOR SMART GRID ANOMALY DETECTION Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Jennifer Rogers;
975	Multi-View Industrial Anomaly Detection with Epipolar Constrained Cross-View Fusion Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this work, we introduce an epipolar geometry-constrained attention module to guide cross-view fusion, ensuring more effective information aggregation.	Yifan Liu; Xun Xu; Shijie Li; Jingyi Liao; Xulei Yang;	arxiv-cs.CV	2025-03-14
976	A GNN-Based False Data Detection Scheme for Smart Grids IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: A Cyber-Physical System (CPS) incorporates communication dynamics and software into phsical processes, providing abstractions, modeling, design, and analytical techniques for the …	JUNHONG QIU et. al.	Algorithms	2025-03-14
977	TSMixAD: A Time-Series Anomaly Detection Framework for Industrial Control Systems Incorporating Time-Frequency Domain Data Augmentation Techniques Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Industrial control systems are an important part of the nation’s critical infrastructure, and effective anomaly detection is important to ensure system safety. However, the …	Yunkai Song; Huihui Huang; Qiang Wei; Lu Liu; Zihan Wei;	Proceedings of the 2025 6th International Conference on …	2025-03-14
978	Memristor-Based Neuromorphic System for Unsupervised Online Learning and Network Anomaly Detection on Edge Devices Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: An ultralow-power, high-performance online-learning and anomaly-detection system has been developed for edge security applications. Designed to support personalized learning …	M. Alam; C. Yakopcic; Raqibul Hasan; Tarek M. Taha;	Information	2025-03-13
979	Anomaly Detection in IoT Networks Using Graph Neural Networks Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Gayathri M; Vanapalli Veera Snigdha; Yendreddy Jayadurga;	2025 7th International Conference on Intelligent …	2025-03-12
980	Feature Analysis and Selection for BGP Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Automated incidence reporting requires accurate and timely anomaly detection. This paper considers this in the context of the Border Gateway Protocol (BGP). BGP is crucial for …	Rifqy Hakimi; Martin J. Reed;	2025 28th Conference on Innovation in Clouds, Internet and …	2025-03-11
981	Enhanced Anomaly Detection in IoT Through Transformer-Based Adversarial Perturbations Model IF:3 Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Ensuring data security in IoT systems requires effective anomaly detection, particularly in multivariate time series data generated by sensor networks. This study introduces a …	Saher Zia; Nargis Bibi; Samah Alhazmi; Nazeer Muhammad; Afnan Alhazmi;	Electronics	2025-03-10
982	An Anomaly Detection Scheme for Data Stream in Cold Chain Logistics Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Anomaly detection is widely used in cold chain logistics (CCL). But, because of the high cost and technical problem, the anomaly detection performance is poor, and the anomaly can …	Zhibo Xie; Heng Long; Chengyi Ling; Yingjun Zhou; Yan Luo;	PloS one	2025-03-10
983	Density-aware and Cluster-based Federated Anomaly Detection on Data Streams Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Federated active anomaly detection on data streams becomes a crucial research problem, since it attempts to discover anomalous data with protecting data privacy and avoiding …	Bin Li; Li Cheng; Zheng Qin; Yunlong Wu;	Proceedings of the Eighteenth ACM International Conference …	2025-03-10
984	AA-CLIP: Enhancing Zero-shot Anomaly Detection Via Anomaly-Aware CLIP IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: While CLIP shows promise for zero-shot AD tasks due to its strong generalization capabilities, its inherent Anomaly-Unawareness leads to limited discrimination between normal and abnormal features. To address this problem, we propose Anomaly-Aware CLIP (AA-CLIP), which enhances CLIP’s anomaly discrimination ability in both text and visual spaces while preserving its generalization capability.	WENXIN MA et. al.	arxiv-cs.CV	2025-03-09
985	Swift Hydra: Self-Reinforcing Generative Framework for Anomaly Detection with Multiple Mamba Models Related Papers Related Patents Related Grants Related Venues Related Experts Related Code View Save Highlight: Despite a plethora of anomaly detection models developed over the years, their ability to generalize to unseen anomalies remains an issue, particularly in critical systems. This paper aims to address this challenge by introducing Swift Hydra, a new framework for training an anomaly detection method based on generative AI and reinforcement learning (RL).	NGUYEN DO et. al.	arxiv-stat.ML	2025-03-08
986	Local Salient Location-aware Anomaly Mask Synthesis for Pulmonary Disease Anomaly Detection and Lesion Localization in CT Images Related Papers Related Patents Related Grants Related Venues Related Experts View Save	HUAYING HAO et. al.	Medical image analysis	2025-03-07
987	Detection of Anomalies in Data Streams Using The LSTM-CNN Model IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a comparative analysis of selected deep learning methods applied to anomaly detection in data streams.	Agnieszka Duraj; Piotr S Szczepaniak; Artur Sadok;	Sensors (Basel, Switzerland)	2025-03-06
988	Hybrid Motion Vector and Deep Learning Approach for Crime Event Detection and Face Identification in Surveillance Footage Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The identification of unusual occurrences is one of the primary goals of the research and use of video surveillance. The objective of enhancing public safety through increased …	R. Dhivya; V. Ajay; P. Dheena; P. Madhavan; S. Meiarul;	2025 5th International Conference on Expert Clouds and …	2025-03-06
989	Improved Anomaly Characterization in Biological Tissues Through Relative Permittivity Estimation Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Microwave imaging for biomedical applications still suffers from imprecise reconstruction of the relative permittivity (εr) of tissues. Most of the traditional methods employing …	Raj Rakshit; Anwesha Khasnobish; Annesha Mazumder; Tapas Chakravarty;	Annual International Conference of the IEEE Engineering in …	2025-03-05
990	Unsupervised Anomaly Detection By Learning Elastic Transformations Within An Autoencoder Approach Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Machine learning has approached magnetic resonance image (MRI) analysis using multiple techniques, including deep supervised learning methodologies, where lesions such as tumors …	ANDRES JIMENEZ-GARCIA et. al.	Annual International Conference of the IEEE Engineering in …	2025-03-05
991	Anomaly Detection in Pediatric and Adults Brain MRI with Generative Model Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: Magnetic Resonance Imaging (MRI) serves as a valuable tool for detecting abnormalities in brain structures. However, a notable 5-10% of pathologies remain unnoticed in MRI scans. …	Chaojun Chen; Khashayar Namdar; Matthias W Wagner; Birgit B Ertl-Wagner; Farzad Khalvati;	Annual International Conference of the IEEE Engineering in …	2025-03-05
992	Big Data-Driven Financial Fraud Detection and Anomaly Detection Systems for Regulatory Compliance and Market Stability IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save		International Journal of Computer Applications Technology …	2025-03-05
993	RAAD-LLM: Adaptive Anomaly Detection Using LLMs and RAG Integration IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we present RAAD-LLM, a novel framework for adaptive anomaly detection, leveraging large language models (LLMs) integrated with Retrieval-Augmented Generation (RAG).	ALICIA RUSSELL-GILBERT et. al.	arxiv-cs.LG	2025-03-04
994	Network Anomaly Detection for IoT Using Hyperdimensional Computing on NSL-KDD IF:3 Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: This paper presents a novel approach to network anomaly detection using hyperdimensional computing (HDC) techniques, specifically applied to the NSL-KDD dataset.	Ghazal Ghajari; Ashutosh Ghimire; Elaheh Ghajari; Fathi Amsaad;	arxiv-cs.CR	2025-03-04
995	Learning Decision Boundaries for Multidimensional Anomaly Detection Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: In this article, we attempt to study a problem of identifying outliers from multiple dimensions, terming it as multidimensional anomaly detection. This task assumes that each …	Xinye Wang; Lei Duan; Lili Guan; Jiaxuan Xu; Chengxin He;	IEEE transactions on neural networks and learning systems	2025-03-03
996	Anomaly Detection in Non-stationary Videos Using Time-recursive Differencing Network Based Prediction Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: In this paper, we propose to perform prediction using a time-recursive differencing network followed by autoregressive moving average estimation for video anomaly detection.	Gargi V. Pillai; Debashis Sen;	arxiv-cs.CV	2025-03-03
997	PA-CLIP: Enhancing Zero-Shot Anomaly Detection Through Pseudo-Anomaly Awareness Related Papers Related Patents Related Grants Related Venues Related Experts View Save Highlight: Traditional approaches often struggle with high false-positive rates, frequently misclassifying normal shadows and surface deformations as defects, an issue that becomes particularly pronounced in products with complex and intricate surface features. To address these challenges, we introduce PA-CLIP, a zero-shot anomaly detection method that reduces background noise and enhances defect detection through a pseudo-anomaly-based framework.	YURUI PAN et. al.	arxiv-cs.CV	2025-03-03
998	Multiscale Recovery Diffusion Model With Unsupervised Learning for Video Anomaly Detection System Summary Related Papers Related Patents Related Grants Related Venues Related Experts View Save Abstract: The rapid development of intelligent industry and smart city increases the number of surveillance devices, greatly enhancing the need for unsupervised automatic anomaly detection …	Bo Li; Hongwei Ge; Yuxuan Liu; Guozhi Tang;	IEEE Transactions on Industrial Informatics	2025-03-01
999	SRAD: A Spatially-aware Reconstruction Network with Anomaly Suppression for Multi-class Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	SHUYUN LI et. al.	Neurocomputing	2025-03-01
1000	Fusion-restoration Model for Industrial Multimodal Anomaly Detection Related Papers Related Patents Related Grants Related Venues Related Experts View Save	Jiaxun Wang; Yanchang Niu; Biqing Huang;	Neurocomputing	2025-03-01