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 1501–1525 of 4856 papers

TitleStatusHype
Decentralized Federated Learning Preserves Model and Data Privacy—0
Decentralized Federated Anomaly Detection in Smart Grids: A P2P Gossip Approach—0
An On-Device Federated Learning Approach for Cooperative Model Update between Edge Devices—0
Decentralized Collaborative Learning Framework with External Privacy Leakage Analysis—0
Deep learning guided Android malware and anomaly detection—0
Dealing with Imbalanced Classes in Bot-IoT Dataset—0
Deep Learning, Machine Learning, Advancing Big Data Analytics and Management—0
Deep learning models for predictive maintenance: a survey, comparison, challenges and prospect—0
Deep Learning Models for Visual Inspection on Automotive Assembling Line—0
Deep Learning on Operational Facility Data Related to Large-Scale Distributed Area Scientific Workflows—0
Deep Learning Serves Traffic Safety Analysis: A Forward-looking Review—0
Deep Multi-Task Learning for Anomalous Driving Detection Using CAN Bus Scalar Sensor Data—0
Deep Nearest Neighbor Anomaly Detection—0
Appearance Blur-driven AutoEncoder and Motion-guided Memory Module for Video Anomaly Detection—0
AnomMAN: Detect Anomaly on Multi-view Attributed Networks—0
DDR-ID: Dual Deep Reconstruction Networks Based Image Decomposition for Anomaly Detection—0
Deep Predictive Coding Neural Network for RF Anomaly Detection in Wireless Networks—0
Deep Probabilistic Modeling of User Behavior for Anomaly Detection via Mixture Density Networks—0
DDMT: Denoising Diffusion Mask Transformer Models for Multivariate Time Series Anomaly Detection—0
DeepQC: A Deep Learning System for Automatic Quality Control of In-situ Soil Moisture Sensor Time Series Data—0
Deep RAN: A Scalable Data-driven platform to Detect Anomalies in Live Cellular Network Using Recurrent Convolutional Neural Network—0
Deep Random Projection Outlyingness for Unsupervised Anomaly Detection—0
Deep-RBF Networks for Anomaly Detection in Automotive Cyber-Physical Systems—0
Anomize: Better Open Vocabulary Video Anomaly Detection—0
DCOR: Anomaly Detection in Attributed Networks via Dual Contrastive Learning Reconstruction—0
Show:102550
← PrevPage 61 of 195Next →
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