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 39764000 of 4856 papers

TitleStatusHype
Hybrid Attention Networks for Flow and Pressure Forecasting in Water Distribution Systems0
A Survey of Single-Scene Video Anomaly Detection0
Towards Anomaly Detection in Dashcam Videos0
Anomaly Detection for Time Series Using VAE-LSTM Hybrid ModelCode1
Anomaly Detection with SDAE0
A Characteristic Function for Shapley-Value-Based Attribution of Anomaly ScoresCode0
Comparison of Evolving Granular Classifiers applied to Anomaly Detection for Predictive Maintenance in Computing Centers0
Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative StudyCode1
pAElla: Edge-AI based Real-Time Malware Detection in Data CentersCode0
Challenges in Vessel Behavior and Anomaly Detection: From Classical Machine Learning to Deep Learning0
When, Where, and What? A New Dataset for Anomaly Detection in Driving VideosCode1
Moving Metric Detection and Alerting System at eBay0
ReRe: A Lightweight Real-time Ready-to-Go Anomaly Detection Approach for Time Series0
Any-Shot Sequential Anomaly Detection in Surveillance Videos0
Anomaly Detection and Prototype Selection Using Polyhedron CurvatureCode0
Using Large-Scale Anomaly Detection on Code to Improve Kotlin CompilerCode0
Video Anomaly Detection for Smart Surveillance0
Anomaly Detection in Univariate Time-series: A Survey on the State-of-the-Art0
Learning Memory-guided Normality for Anomaly DetectionCode1
Introduction to Rare-Event Predictive Modeling for Inferential Statisticians -- A Hands-On Application in the Prediction of Breakthrough PatentsCode0
SiTGRU: Single-Tunnelled Gated Recurrent Unit for Abnormality Detection0
One-Shot GAN Generated Fake Face Detection0
ABBA: Adaptive Brownian bridge-based symbolic aggregation of time series0
Viral Pneumonia Screening on Chest X-ray Images Using Confidence-Aware Anomaly DetectionCode1
FastDTW is approximate and Generally Slower than the Algorithm it ApproximatesCode1
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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