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 1726–1750 of 4856 papers

TitleStatusHype
Domain-Generalized Textured Surface Anomaly Detection—0
Data-Driven Thermal Anomaly Detection in Large Battery Packs—0
ACE -- An Anomaly Contribution Explainer for Cyber-Security Applications—0
A Comparison of Deep Learning Architectures for Spacecraft Anomaly Detection—0
DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN—0
DoS and DDoS Mitigation Using Variational Autoencoders—0
A Survey of Time Series Anomaly Detection Methods in the AIOps Domain—0
Data Drift Monitoring for Log Anomaly Detection Pipelines—0
DPOAD: Differentially Private Outsourcing of Anomaly Detection through Iterative Sensitivity Learning—0
Data Cleaning for XML Electronic Dictionaries via Statistical Anomaly Detection—0
Analyzing Business Process Anomalies Using Autoencoders—0
DRAM Failure Prediction in AIOps: Empirical Evaluation, Challenges and Opportunities—0
Drifter: Efficient Online Feature Monitoring for Improved Data Integrity in Large-Scale Recommendation Systems—0
Data Augmentation by AutoEncoders for Unsupervised Anomaly Detection—0
Driver Age and Its Effect on Key Driving Metrics: Insights from Dynamic Vehicle Data—0
Data augmentation and pre-trained networks for extremely low data regimes unsupervised visual inspection—0
ADEPOS: A Novel Approximate Computing Framework for Anomaly Detection Systems and its Implementation in 65nm CMOS—0
Data Anomaly Detection for Structural Health Monitoring of Bridges using Shapelet Transform—0
Data-Agnostic Face Image Synthesis Detection Using Bayesian CNNs—0
Anomaly Locality in Video Surveillance—0
DAS3D: Dual-modality Anomaly Synthesis for 3D Anomaly Detection—0
Analytics and Machine Learning Powered Wireless Network Optimization and Planning—0
Ensemble Grammar Induction For Detecting Anomalies in Time Series—0
Ensemble Learning based Anomaly Detection for IoT Cybersecurity via Bayesian Hyperparameters Sensitivity Analysis—0
Dance With Self-Attention: A New Look of Conditional Random Fields on Anomaly Detection in Videos—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