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 2876–2900 of 4856 papers

TitleStatusHype
Learning to Detect Interesting Anomalies—0
Anomaly Detection in Additive Manufacturing Processes using Supervised Classification with Imbalanced Sensor Data based on Generative Adversarial Network—0
Deep Learning-Based Anomaly Detection in Synthetic Aperture Radar Imaging—0
Masked Transformer for image Anomaly Localization—0
Data-Driven Thermal Anomaly Detection in Large Battery Packs—0
Spatio-temporal predictive tasks for abnormal event detection in videos—0
A Hierarchical Approach to Conditional Random Fields for System Anomaly Detection—0
AD-DMKDE: Anomaly Detection through Density Matrices and Fourier FeaturesCode0
AltUB: Alternating Training Method to Update Base Distribution of Normalizing Flow for Anomaly Detection—0
Detecting fake accounts through Generative Adversarial Network in online social media—0
Deep Crowd Anomaly Detection: State-of-the-Art, Challenges, and Future Research Directions—0
InForecaster: Forecasting Influenza Hemagglutinin Mutations Through the Lens of Anomaly DetectionCode0
Bridging Machine Learning and Sciences: Opportunities and Challenges—0
Multi-Scale Patch-Based Representation Learning for Image Anomaly Detection and Segmentation—0
Improving the Anomaly Detection in GPR Images by Fine-Tuning CNNs with Synthetic Data—0
Frequency of Interest-based Noise Attenuation Method to Improve Anomaly Detection Performance—0
ADPS: Asymmetric Distillation Post-Segmentation for Image Anomaly Detection—0
Time and Cost-Efficient Bathymetric Mapping System using Sparse Point Cloud Generation and Automatic Object DetectionCode0
Hierarchical Deep Learning with Generative Adversarial Network for Automatic Cardiac Diagnosis from ECG Signals—0
Spatio-Temporal-based Context Fusion for Video Anomaly Detection—0
N-pad : Neighboring Pixel-based Industrial Anomaly Detection—0
CAN-BERT do it? Controller Area Network Intrusion Detection System based on BERT Language Model—0
Towards Generating Adversarial Examples on Mixed-type Data—0
tegdet: An extensible Python Library for Anomaly Detection using Time-Evolving GraphsCode0
Autoencoder based Anomaly Detection and Explained Fault Localization in Industrial Cooling Systems—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
6INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
7DDADDetection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9PBASDetection AUROC99.8—Unverified
10HETMMDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4DDADDetection AUROC98.9—Unverified
5Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
6INP-Former ViT-B (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