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

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Showing 1701–1750 of 4856 papers

TitleStatusHype
BiGSeT: Binary Mask-Guided Separation Training for DNN-based Hyperspectral Anomaly DetectionCode0
Synthetic Data Generation for Anomaly Detection on Table GrapesCode0
Effect of Deep Transfer and Multi task Learning on Sperm Abnormality DetectionCode0
Action Sequence Augmentation for Early Graph-based Anomaly DetectionCode0
E-ABIN: an Explainable module for Anomaly detection in BIological NetworksCode0
DISYRE: Diffusion-Inspired SYnthetic REstoration for Unsupervised Anomaly DetectionCode0
Early Anomaly Detection in Time Series: A Hierarchical Approach for Predicting Critical Health EpisodesCode0
Adaptive NAD: Online and Self-adaptive Unsupervised Network Anomaly DetectorCode0
Early-Stage Anomaly Detection: A Study of Model Performance on Complete vs. Partial FlowsCode0
A Study of Representational Properties of Unsupervised Anomaly Detection in Brain MRICode0
β-GNN: A Robust Ensemble Approach Against Graph Structure PerturbationCode0
Dynamic Erasing Network Based on Multi-Scale Temporal Features for Weakly Supervised Video Anomaly DetectionCode0
Beyond the Benchmark: Detecting Diverse Anomalies in VideosCode0
Dlib-ml: A Machine Learning ToolkitCode0
Beyond Single-Modal Boundary: Cross-Modal Anomaly Detection through Visual Prototype and HarmonizationCode0
Temporal anomaly detection: calibrating the surpriseCode0
Tensor Network for Anomaly Detection in the Latent Space of Proton Collision Events at the LHCCode0
Beyond Sharing: Conflict-Aware Multivariate Time Series Anomaly DetectionCode0
AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection ApproachCode0
Dual-Modality Vehicle Anomaly Detection via Bilateral Trajectory TracingCode0
Coupled-Space Attacks against Random-Walk-based Anomaly DetectionCode0
Beyond Conventional Transformers: The Medical X-ray Attention (MXA) Block for Improved Multi-Label Diagnosis Using Knowledge DistillationCode0
Beyond Academic Benchmarks: Critical Analysis and Best Practices for Visual Industrial Anomaly DetectionCode0
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated LearningCode0
Domain Adaptive and Fine-grained Anomaly Detection for Single-cell Sequencing Data and BeyondCode0
The Impact of Discretization Method on the Detection of Six Types of Anomalies in DatasetsCode0
Benchmarking Unsupervised Strategies for Anomaly Detection in Multivariate Time SeriesCode0
DTOR: Decision Tree Outlier Regressor to explain anomaliesCode0
Benchmarking Suite for Synthetic Aperture Radar Imagery Anomaly Detection (SARIAD) AlgorithmsCode0
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed GraphsCode0
Individualized multi-horizon MRI trajectory prediction for Alzheimer's DiseaseCode0
Double-Adversarial Activation Anomaly Detection: Adversarial Autoencoders are Anomaly GeneratorsCode0
TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly DetectionCode0
Large Models in Dialogue for Active Perception and Anomaly DetectionCode0
Prioritizing Alignment Paradigms over Task-Specific Model Customization in Time-Series LLMsCode0
Benchmarking energy consumption and latency for neuromorphic computing in condensed matter and particle physics—0
Anomaly Detection in 3D Point Clouds using Deep Geometric Descriptors—0
Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning—0
A geometric framework for outlier detection in high-dimensional data—0
Bayesian Time Series Forecasting with Change Point and Anomaly Detection—0
Anomaly Detection from a Tensor Train Perspective—0
Bayesian Optimization with Machine Learning Algorithms Towards Anomaly Detection—0
Anomaly Detection Framework Using Rule Extraction for Efficient Intrusion Detection—0
A Generic Machine Learning Framework for Fully-Unsupervised Anomaly Detection with Contaminated Data—0
Bayesian Learning of Clique Tree Structure—0
Anomaly Detection for Water Treatment System based on Neural Network with Automatic Architecture Optimization—0
Bayesian Hypernetworks—0
Bayesian generative models can flag performance loss, bias, and out-of-distribution image content—0
Anomaly Detection for Unmanned Aerial Vehicle Sensor Data Using a Stacked Recurrent Autoencoder Method with Dynamic Thresholding—0
A general-purpose method for applying Explainable AI for Anomaly Detection—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