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 31013125 of 4856 papers

TitleStatusHype
CloudRCA: A Root Cause Analysis Framework for Cloud Computing Platforms0
A Personalized Federated Learning Algorithm: an Application in Anomaly Detection0
Towards Smart Monitored AM: Open Source in-Situ Layer-wise 3D Printing Image Anomaly Detection Using Histograms of Oriented Gradients and a Physics-Based Rendering Engine0
Automated, real-time hospital ICU emergency signaling: A field-level implementation0
A Critical Study on the Recent Deep Learning Based Semi-Supervised Video Anomaly Detection Methods0
Markus Thill Temporal convolutional autoencoder for unsupervised anomaly detection in time series0
TADPOLE: Task ADapted Pre-Training via AnOmaLy DEtection0
Semantic Novelty Detection in Natural Language DescriptionsCode0
A Modified Dynamic Time Warping (MDTW) Approach and Innovative Average Non-Self Match Distance (ANSD) Method for Anomaly Detection in ECG Recordings0
Real-Time Detection of Anomalies in Large-Scale Transient Surveys0
Evaluation of an Anomaly Detector for Routers using Parameterizable Malware in an IoT Ecosystem0
Boosting Anomaly Detection Using Unsupervised Diverse Test-Time AugmentationCode0
PEDENet: Image Anomaly Localization via Patch Embedding and Density Estimation0
How to boost autoencoders?0
Multi-Class Anomaly Detection0
OMASGAN: Out-of-Distribution Minimum Anomaly Score GAN for Sample Generation on the BoundaryCode1
Normality-Calibrated Autoencoder for Unsupervised Anomaly Detection on Data ContaminationCode0
Anomaly-Injected Deep Support Vector Data Description for Text Outlier Detection0
Sensing Anomalies as Potential Hazards: Datasets and BenchmarksCode1
Subtractive Aggregation for Attributed Network Anomaly DetectionCode0
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future ChallengesCode1
Revisiting randomized choices in isolation forests0
Patch vs. Global Image-Based Unsupervised Anomaly Detection in MR Brain Scans of Early Parkinsonian Patients0
Practical Galaxy Morphology Tools from Deep Supervised Representation LearningCode1
Pediatric Otoscopy Video Screening with Shift Contrastive Anomaly Detection0
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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