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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2101–2125 of 4856 papers

TitleStatusHype
A Taxonomy of Anomalies in Log Data—0
Early Anomaly Detection in Power Systems Based on Random Matrix Theory—0
Anomaly Detection And Classification In Time Series With Kervolutional Neural Networks—0
Early Abnormal Detection of Sewage Pipe Network: Bagging of Various Abnormal Detection Algorithms—0
EAPCR: A Universal Feature Extractor for Scientific Data without Explicit Feature Relation Patterns—0
A task of anomaly detection for a smart satellite Internet of things system—0
EAGLE: Contrastive Learning for Efficient Graph Anomaly Detection—0
eACGM: Non-instrumented Performance Tracing and Anomaly Detection towards Machine Learning Systems—0
A Tale of Two Latent Flows: Learning Latent Space Normalizing Flow with Short-run Langevin Flow for Approximate Inference—0
Anomaly Detection and Classification in Knowledge Graphs—0
Adversarial Pseudo Healthy Synthesis Needs Pathology Factorization—0
Dysarthric speech evaluation: automatic and perceptual approaches—0
ATAC-Net: Zoomed view works better for Anomaly Detection—0
DynamoPMU: A Physics Informed Anomaly Detection and Prediction Methodology using non-linear dynamics from μPMU Measurement Data—0
A Systematic Review of Machine Learning in Sports Betting: Techniques, Challenges, and Future Directions—0
Anomaly detection and classification for streaming data using PDEs—0
Dynamic Interactional And Cooperative Network For Shield Machine—0
A Systematic Mapping Study in AIOps—0
Dynamic Graph Embedding via LSTM History Tracking—0
A systematic literature review of unsupervised learning algorithms for anomalous traffic detection based on flows—0
Anomaly detection and automatic labeling for solar cell quality inspection based on Generative Adversarial Network—0
Adversarial Machine Learning Threat Analysis and Remediation in Open Radio Access Network (O-RAN)—0
A Synergy Scoring Filter for Unsupervised Anomaly Detection with Noisy Data—0
Anomaly Detection and Automated Labeling for Voter Registration File Changes—0
Dynamic Bayesian Approach for decision-making in Ego-Things—0
Show:102550
← PrevPage 85 of 195Next →
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