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 15511600 of 4856 papers

TitleStatusHype
Exploring Deep Anomaly Detection Methods Based on Capsule NetCode0
Explaining Anomalies in Groups with Characterizing Subspace RulesCode0
Exploring Hyperspectral Anomaly Detection with Human Vision: A Small Target Aware DetectorCode0
A predictive model for the identification of learning styles in MOOC environmentsCode0
Explainable Machine Learning for Cyberattack Identification from Traffic FlowsCode0
Explainable Differential Privacy-Hyperdimensional Computing for Balancing Privacy and Transparency in Additive Manufacturing MonitoringCode0
Explainable Online Unsupervised Anomaly Detection for Cyber-Physical Systems via Causal Discovery from Time SeriesCode0
Explain First, Trust Later: LLM-Augmented Explanations for Graph-Based Crypto Anomaly DetectionCode0
Explainable Anomaly Detection for Industrial Control System CybersecurityCode0
Experiment-based detection of service disruption attacks in optical networks using data analytics and unsupervised learningCode0
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly DetectionCode0
Exact Optimization of Conformal Predictors via Incremental and Decremental LearningCode0
Enhancing Interpretability and Generalizability in Extended Isolation ForestsCode0
Evidential Deep Learning for Uncertainty Quantification and Out-of-Distribution Detection in Jet Identification using Deep Neural NetworksCode0
Evaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative models: Application to brain FDG PETCode0
Exact Matrix Seriation through Mathematical Optimization: Stress and Effectiveness-Based ModelsCode0
Expected Similarity Estimation for Large-Scale Batch and Streaming Anomaly DetectionCode0
Explainable Debugger for Black-box Machine Learning ModelsCode0
Can Tree Based Approaches Surpass Deep Learning in Anomaly Detection? A Benchmarking StudyCode0
Anomaly Detection in Networks via Score-Based Generative ModelsCode0
Evaluating ML-Based Anomaly Detection Across Datasets of Varied Integrity: A Case StudyCode0
Anomaly Detection in Multivariate Non-stationary Time Series for Automatic DBMS DiagnosisCode0
Evaluating Language Models For Threat Detection in IoT Security LogsCode0
Detecting Anomalies in Image Classification by Means of Semantic RelationshipsCode0
Estimate the Implicit Likelihoods of GANs with Application to Anomaly DetectionCode0
Evaluating Bayesian Deep Learning Methods for Semantic SegmentationCode0
Evaluating the Ability of LLMs to Solve Semantics-Aware Process Mining TasksCode0
Can I trust my anomaly detection system? A case study based on explainable AICode0
Ensembled Cold-Diffusion Restorations for Unsupervised Anomaly DetectionCode0
Enhancing Wrist Fracture Detection with YOLOCode0
Ensemble Clustering for Graphs: Comparisons and ApplicationsCode0
Equipping Computational Pathology Systems with Artifact Processing Pipelines: A Showcase for Computation and Performance Trade-offsCode0
Enhancing Time Series Forecasting with Fuzzy Attention-Integrated TransformersCode0
Enhancing Unsupervised Anomaly Detection with Score-Guided NetworkCode0
Anomaly Detection in Large-Scale Cloud Systems: An Industry Case and DatasetCode0
Enhancing Robustness of On-line Learning Models on Highly Noisy DataCode0
Enhancing Visual Perception in Novel Environments via Incremental Data Augmentation Based on Style TransferCode0
Evaluating Vision Transformer Models for Visual Quality Control in Industrial ManufacturingCode0
PyScrew: A Comprehensive Dataset Collection from Industrial Screw Driving ExperimentsCode0
Enhanced anomaly detection in well log data through the application of ensemble GANsCode0
TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly DetectionCode0
Quantum-probabilistic Hamiltonian learning for generative modelling & anomaly detectionCode0
Enhancing Anomaly Detection Generalization through Knowledge Exposure: The Dual Effects of AugmentationCode0
CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive LearningCode0
Enabling Efficient and Flexible Interpretability of Data-driven Anomaly Detection in Industrial Processes with AcME-ADCode0
ENCODE: Encoding NetFlows for Network Anomaly DetectionCode0
Adaptive Deviation Learning for Visual Anomaly Detection with Data ContaminationCode0
Eloss in the way: A Sensitive Input Quality Metrics for Intelligent DrivingCode0
Enhancing Fairness in Unsupervised Graph Anomaly Detection through DisentanglementCode0
Efficient Model Monitoring for Quality Control in Cardiac Image SegmentationCode0
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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