SOTAVerified

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 1776–1800 of 4856 papers

TitleStatusHype
Cyber-Attack Event Analysis for EV Charging Stations—0
Dynamic Interactional And Cooperative Network For Shield Machine—0
Cyber Anomaly Detection Using Graph-node Role-dynamics—0
A Systematic Review of Machine Learning in Sports Betting: Techniques, Challenges, and Future Directions—0
DynamoPMU: A Physics Informed Anomaly Detection and Prediction Methodology using non-linear dynamics from μPMU Measurement Data—0
Dysarthric speech evaluation: automatic and perceptual approaches—0
ATAC-Net: Zoomed view works better for Anomaly Detection—0
eACGM: Non-instrumented Performance Tracing and Anomaly Detection towards Machine Learning Systems—0
EAGLE: Contrastive Learning for Efficient Graph Anomaly Detection—0
EAPCR: A Universal Feature Extractor for Scientific Data without Explicit Feature Relation Patterns—0
Early Abnormal Detection of Sewage Pipe Network: Bagging of Various Abnormal Detection Algorithms—0
A comparison of classical and variational autoencoders for anomaly detection—0
Early Anomaly Detection in Power Systems Based on Random Matrix Theory—0
A Taxonomy of Anomalies in Log Data—0
Early Cancer Detection in Blood Vessels Using Mobile Nanosensors—0
Experiments on Anomaly Detection in Autonomous Driving by Forward-Backward Style Transfers—0
Explainable Anomaly Detection: Counterfactual driven What-If Analysis—0
Early Warning Signals of Social Instabilities in Twitter Data—0
EasyNet: An Easy Network for 3D Industrial Anomaly Detection—0
EB-GAME: A Game-Changer in ECG Heartbeat Anomaly Detection—0
ECATS: Explainable-by-design concept-based anomaly detection for time series—0
ECG classification using Deep CNN and Gramian Angular Field—0
ECG Signal Preprocessing and SVM Classifier-Based Abnormality Detection in Remote Healthcare Applications—0
ECNN: A Low-complex, Adjustable CNN for Industrial Pump Monitoring Using Vibration Data—0
CXR-AD: Component X-ray Image Dataset for Industrial Anomaly Detection—0
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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