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

Showing 11261150 of 4856 papers

TitleStatusHype
Anomaly Detection and Inter-Sensor Transfer Learning on Smart Manufacturing Datasets0
A Time Series Multitask Framework Integrating a Large Language Model, Pre-Trained Time Series Model, and Knowledge Graph0
Anomaly Detection and Interpretation using Multimodal Autoencoder and Sparse Optimization0
Adversarial vs behavioural-based defensive AI with joint, continual and active learning: automated evaluation of robustness to deception, poisoning and concept drift0
Abnormal Client Behavior Detection in Federated Learning0
A Theoretical Investigation of Graph Degree as an Unsupervised Normality Measure0
A Theoretical Framework for AI-driven data quality monitoring in high-volume data environments0
Anomaly Detection and Inlet Pressure Prediction in Water Distribution Systems Using Machine Learning0
A Temporal Anomaly Detection System for Vehicles utilizing Functional Working Groups and Sensor Channels0
Anomaly Detection and Improvement of Clusters using Enhanced K-Means Algorithm0
Adversarial Sample Generation for Anomaly Detection in Industrial Control Systems0
Convolutional Recurrent Reconstructive Network for Spatiotemporal Anomaly Detection in Solder Paste Inspection0
cOOpD: Reformulating COPD classification on chest CT scans as anomaly detection using contrastive representations0
Copula-based anomaly scoring and localization for large-scale, high-dimensional continuous data0
Correlated Attention in Transformers for Multivariate Time Series0
Cross Attention Transformers for Multi-modal Unsupervised Whole-Body PET Anomaly Detection0
A Taxonomy of Anomalies in Log Data0
Anomaly Detection And Classification In Time Series With Kervolutional Neural Networks0
Adversarial Pseudo Healthy Synthesis Needs Pathology Factorization0
A task of anomaly detection for a smart satellite Internet of things system0
A Tale of Two Latent Flows: Learning Latent Space Normalizing Flow with Short-run Langevin Flow for Approximate Inference0
Anomaly Detection and Classification in Knowledge Graphs0
Adversarial Machine Learning Threat Analysis and Remediation in Open Radio Access Network (O-RAN)0
ATAC-Net: Zoomed view works better for Anomaly Detection0
A Systematic Review of Machine Learning in Sports Betting: Techniques, Challenges, and Future Directions0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016Unverified
2CPR-fast(TensorRT)FPS362Unverified
3CPR(TensorRT)FPS130Unverified
4GLASSDetection AUROC99.9Unverified
5UniNetDetection AUROC99.9Unverified
6HETMMDetection AUROC99.8Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8Unverified
8EfficientAD (early stopping)Detection AUROC99.8Unverified
9DDADDetection AUROC99.8Unverified
10PBASDetection AUROC99.8Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8Unverified
2GLADDetection AUROC99.5Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9Unverified
5DDADDetection AUROC98.9Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9Unverified
7DiffusionADDetection AUROC98.8Unverified
8GLASSDetection AUROC98.8Unverified
9TransFusionDetection AUROC98.7Unverified
10HETMMDetection AUROC98.1Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3Unverified
2PSADAvg. Detection AUROC94.9Unverified