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Anomaly Detection

Anomaly Detection is a binary classification identifying unusual or unexpected patterns in a dataset, which deviate significantly from the majority of the data. The goal of anomaly detection is to identify such anomalies, which could represent errors, fraud, or other types of unusual events, and flag them for further investigation.

[Image source]: GAN-based Anomaly Detection in Imbalance Problems

Papers

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Showing 4751–4800 of 4856 papers

TitleStatusHype
Sliced-Wasserstein-based Anomaly Detection and Open Dataset for Localized Critical Peak RebatesCode0
Enhancing Fairness in Unsupervised Graph Anomaly Detection through DisentanglementCode0
A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series DataCode0
Context Recovery and Knowledge Retrieval: A Novel Two-Stream Framework for Video Anomaly DetectionCode0
Pre-training Vision Models with Mandelbulb VariationsCode0
Unsupversied feature correlation model to predict breast abnormal variation maps in longitudinal mammogramsCode0
Prioritizing Alignment Paradigms over Task-Specific Model Customization in Time-Series LLMsCode0
ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-Variable Context EncodingCode0
Deep Weakly-supervised Anomaly DetectionCode0
CKNN: Cleansed k-Nearest Neighbor for Unsupervised Video Anomaly DetectionCode0
Video Trajectory Classification and Anomaly Detection Using Hybrid CNN-VAECode0
Context Enhancement with Reconstruction as Sequence for Unified Unsupervised Anomaly DetectionCode0
Anomaly Detection in Large-Scale Cloud Systems: An Industry Case and DatasetCode0
Towards Efficient Quantum Anomaly Detection: One-Class SVMs using Variable Subsampling and Randomized MeasurementsCode0
Context-Aware Deep Time-Series Decomposition for Anomaly Detection in BusinessesCode0
Enhancing Anomaly Detection Generalization through Knowledge Exposure: The Dual Effects of AugmentationCode0
A Probabilistic Transformation of Distance-Based OutliersCode0
Anomaly Detection in High Dimensional DataCode0
Anomaly detection in dynamic networksCode0
Smart Vectorizations for Single and Multiparameter PersistenceCode0
ATD: Anomalous Topic Discovery in High Dimensional Discrete DataCode0
A Deep Learning Approach for Active Anomaly Detection of Extragalactic TransientsCode0
Enhanced anomaly detection in well log data through the application of ensemble GANsCode0
Consistency-based anomaly detection with adaptive multiple-hypotheses predictionsCode0
Conformalized Semi-supervised Random Forest for Classification and Abnormality DetectionCode0
Confidence-Aware and Self-Supervised Image Anomaly LocalisationCode0
Anomaly Detection in Cooperative Vehicle Perception Systems under Imperfect CommunicationCode0
TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly DetectionCode0
A Taxonomy of Network Threats and the Effect of Current Datasets on Intrusion Detection SystemsCode0
Towards frugal unsupervised detection of subtle abnormalities in medical imagingCode0
ENCODE: Encoding NetFlows for Network Anomaly DetectionCode0
Prompt-Enhanced Multiple Instance Learning for Weakly Supervised Video Anomaly DetectionCode0
PromptTAD: Object-Prompt Enhanced Traffic Anomaly DetectionCode0
Unsupervised Anomaly Detection Ensembles using Item Response TheoryCode0
Concept Drift and Anomaly Detection in Graph StreamsCode0
A Survey on GANs for Anomaly DetectionCode0
Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive LearningCode0
Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging InfrastructureCode0
A Subspace Method for Time Series Anomaly Detection in Cyber-Physical SystemsCode0
Concentration Inequalities for Two-Sample Rank Processes with Application to Bipartite RankingCode0
Pseudo-healthy synthesis with pathology disentanglement and adversarial learningCode0
Concentration bounds for the empirical angular measure with statistical learning applicationsCode0
Computer Vision and Normalizing Flow-Based Defect DetectionCode0
Learning Invariant Rules from Data for Interpretable Anomaly DetectionCode0
Interpreting Vulnerabilities of Multi-Instance Learning to Adversarial PerturbationsCode0
Enabling Efficient and Flexible Interpretability of Data-driven Anomaly Detection in Industrial Processes with AcME-ADCode0
Addressing the Impact of Localized Training Data in Graph Neural NetworksCode0
Anomaly Detection: How to Artificially Increase your F1-Score with a Biased Evaluation ProtocolCode0
ALFA: A Dataset for UAV Fault and Anomaly DetectionCode0
Zero-bias Deep Learning Enabled Quick and Reliable Abnormality Detection in IoTCode0
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All datasetsMVTec ADVisAMVTec LOCO ADOne-class CIFAR-10CUHK AvenueShanghaiTechFishyscapes L&FUCR Anomaly ArchiveMPDDBTADOne-class CIFAR-100UBnormal

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016—Unverified
2CPR-fast(TensorRT)FPS362—Unverified
3CPR(TensorRT)FPS130—Unverified
4GLASSDetection AUROC99.9—Unverified
5UniNetDetection AUROC99.9—Unverified
6HETMMDetection AUROC99.8—Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9DDADDetection AUROC99.8—Unverified
10PBASDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9—Unverified
5DDADDetection AUROC98.9—Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
7DiffusionADDetection AUROC98.8—Unverified
8GLASSDetection AUROC98.8—Unverified
9TransFusionDetection AUROC98.7—Unverified
10HETMMDetection AUROC98.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3—Unverified
2PSADAvg. Detection AUROC94.9—Unverified