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 2226–2250 of 4856 papers

TitleStatusHype
AddGraph_ Anomaly Detection in Dynamic Graph Using Attention-based Temporal GCN—0
Computer Vision Toolkit for Non-invasive Monitoring of Factory Floor Artifacts—0
Computer Vision on X-ray Data in Industrial Production and Security Applications: A Comprehensive Survey—0
Anomaly Detection through Transfer Learning in Agriculture and Manufacturing IoT Systems—0
Anomaly detection through latent space restoration using vector-quantized variational autoencoders—0
A Massively Parallel Associative Memory Based on Sparse Neural Networks—0
Computer-aided abnormality detection in chest radiographs in a clinical setting via domain-adaptation—0
Compressive Change Retrieval for Moving Object Detection—0
Anomaly Detection Techniques in Smart Grid Systems: A Review—0
ACMamba: Fast Unsupervised Anomaly Detection via An Asymmetrical Consensus State Space Model—0
Grid Monitoring with Synchro-Waveform and AI Foundation Model Technologies—0
Compressed Smooth Sparse Decomposition—0
Anomaly Detection Support Using Process Classification—0
A Marketplace Price Anomaly Detection System at Scale—0
Comprehensible Counterfactual Explanation on Kolmogorov-Smirnov Test—0
Composite Score for Anomaly Detection in Imbalanced Real-World Industrial Dataset—0
Anomaly Detection: Review and preliminary Entropy method tests—0
Greenhouse: A Zero-Positive Machine Learning System for Time-Series Anomaly Detection—0
Composite Kernel Local Angular Discriminant Analysis for Multi-Sensor Geospatial Image Analysis—0
A Mallows-like Criterion for Anomaly Detection with Random Forest Implementation—0
Component-aware Unsupervised Logical Anomaly Generation for Industrial Anomaly Detection—0
Anomaly detection optimization using big data and deep learning to reduce false-positive—0
ADDAI: Anomaly Detection using Distributed AI—0
Group Anomaly Detection using Flexible Genre Models—0
Complying with the EU AI Act: Innovations in Explainable and User-Centric Hand Gesture Recognition—0
Show:102550
← PrevPage 90 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