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 4776–4800 of 4856 papers

TitleStatusHype
Hybrid data-driven physics model-based framework for enhance cyber-physical smart grid security—0
Hybrid Deep Learning Model using SPCAGAN Augmentation for Insider Threat Analysis—0
Hybrid Efficient Unsupervised Anomaly Detection for Early Pandemic Case Identification—0
Hybridization of Capsule and LSTM Networks for unsupervised anomaly detection on multivariate data—0
Hybrid Meta-Learning Framework for Anomaly Forecasting in Nonlinear Dynamical Systems via Physics-Inspired Simulation and Deep Ensembles—0
Hybrid Model for Anomaly Detection on Call Detail Records by Time Series Forecasting—0
Hybrid Temporal Differential Consistency Autoencoder for Efficient and Sustainable Anomaly Detection in Cyber-Physical Systems—0
Hybrid Video Anomaly Detection for Anomalous Scenarios in Autonomous Driving—0
Hyperbolic Anomaly Detection—0
Hyperbolic embedding of brain networks detects regions disrupted by neurodegeneration in Alzheimer's disease—0
Hyperbolic Self-supervised Contrastive Learning Based Network Anomaly Detection—0
Hypergraph-based multi-scale spatio-temporal graph convolution network for Time-Series anomaly detection—0
Hypergraph Learning based Recommender System for Anomaly Detection, Control and Optimization—0
Hyperspectral Anomaly Detection Methods: A Survey and Comparative Study—0
Hyperspectral Anomaly Detection with Self-Supervised Anomaly Prior—0
iADCPS: Time Series Anomaly Detection for Evolving Cyber-physical Systems via Incremental Meta-learning—0
ID-Conditioned Auto-Encoder for Unsupervised Anomaly Detection—0
iDECODe: In-distribution Equivariance for Conformal Out-of-distribution Detection—0
Identification and Characterization for Disruptions in the U.S. National Airspace System (NAS)—0
Identification of Abnormality in Maize Plants From UAV Images Using Deep Learning Approaches—0
Identification of temporal transition of functional states using recurrent neural networks from functional MRI—0
Ignoring Distractors in the Absence of Labels: Optimal Linear Projection to Remove False Positives During Anomaly Detection—0
IGRF-RFE: A Hybrid Feature Selection Method for MLP-based Network Intrusion Detection on UNSW-NB15 Dataset—0
IMAFD: An Interpretable Multi-stage Approach to Flood Detection from time series Multispectral Data—0
Image Anomalies: a Review and Synthesis of Detection Methods—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
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