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 4601–4650 of 4856 papers

TitleStatusHype
A Weighted Mutual k-Nearest Neighbour for Classification MiningCode0
VeeAlign: Multifaceted Context Representation using Dual Attention for Ontology AlignmentCode0
Anomaly Detection in Video Sequence with Appearance-Motion CorrespondenceCode0
OpenOOD: Benchmarking Generalized Out-of-Distribution DetectionCode0
Semi-supervised Anomaly Detection on Attributed GraphsCode0
Cyber Security Data Science: Machine Learning Methods and their Performance on Imbalanced DatasetsCode0
AVID: Adversarial Visual Irregularity DetectionCode0
Open-source FPGA-ML codesign for the MLPerf Tiny BenchmarkCode0
Semi-supervised Anomaly Detection via Adaptive Reinforcement Learning-Enabled Method with Causal Inference for Sensor SignalsCode0
OptIForest: Optimal Isolation Forest for Anomaly DetectionCode0
Optimal Classification-based Anomaly Detection with Neural Networks: Theory and PracticeCode0
Adaptive Anomaly Detection in Chaotic Time Series with a Spatially Aware Echo State NetworkCode0
Facial Behavior Analysis using 4D Curvature Statistics for Presentation Attack DetectionCode0
VELC: A New Variational AutoEncoder Based Model for Time Series Anomaly DetectionCode0
Optimal Strategies Against Generative AttacksCode0
FABLE : Fabric Anomaly Detection Automation ProcessCode0
Semi-supervised Deep Embedded Clustering with Anomaly Detection for Semantic Frame InductionCode0
CVTGAD: Simplified Transformer with Cross-View Attention for Unsupervised Graph-level Anomaly DetectionCode0
Extended Isolation ForestCode0
Unsupervised Representation Learning by Predicting Random DistancesCode0
Semi-Supervised Learning for Anomaly Traffic Detection via Bidirectional Normalizing FlowsCode0
Automatic Hyperparameter Tuning Method for Local Outlier Factor, with Applications to Anomaly DetectionCode0
ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network ApproachCode0
Time series anomaly detection with reconstruction-based state-space modelsCode0
Exploring the Influence of Dimensionality Reduction on Anomaly Detection Performance in Multivariate Time SeriesCode0
Exploring Scalable, Distributed Real-Time Anomaly Detection for Bridge Health MonitoringCode0
Automatic Feature Extraction for Heartbeat Anomaly DetectionCode0
CSE: Surface Anomaly Detection with Contrastively Selected EmbeddingCode0
Automatic Anomaly Detection in the Cloud Via Statistical LearningCode0
Exploring Hyperspectral Anomaly Detection with Human Vision: A Small Target Aware DetectorCode0
Overcoming the Identity Mapping Problem in Self-Supervised Hyperspectral Anomaly DetectionCode0
xSemAD: Explainable Semantic Anomaly Detection in Event Logs Using Sequence-to-Sequence ModelsCode0
Exploring Deep Anomaly Detection Methods Based on Capsule NetCode0
Sensor Data Simulation for Anomaly Detection of the Elderly Living AloneCode0
CSCLog: A Component Subsequence Correlation-Aware Log Anomaly Detection MethodCode0
Time Series Data Cleaning: From Anomaly Detection to Anomaly RepairingCode0
Automated anomaly-aware 3D segmentation of bones and cartilages in knee MR images from the Osteoarthritis InitiativeCode0
Acquiring Better Load Estimates by Combining Anomaly and Change Point Detection in Power Grid Time-series MeasurementsCode0
Explaining Anomalies in Groups with Characterizing Subspace RulesCode0
Explain First, Trust Later: LLM-Augmented Explanations for Graph-Based Crypto Anomaly DetectionCode0
Seq2Seq RNN based Gait Anomaly Detection from Smartphone Acquired Multimodal Motion DataCode0
pAElla: Edge-AI based Real-Time Malware Detection in Data CentersCode0
Time Series Foundational Models: Their Role in Anomaly Detection and PredictionCode0
Explainable Online Unsupervised Anomaly Detection for Cyber-Physical Systems via Causal Discovery from Time SeriesCode0
A Metric Learning Approach to Anomaly Detection in Video GamesCode0
PANDA: Predicting the change in proteins binding affinity upon mutations using sequence informationCode0
Unlocking the Potential of Weakly Labeled Data: A Co-Evolutionary Learning Framework for Abnormality Detection and Report GenerationCode0
Autoencoders and Generative Adversarial Networks for Imbalanced Sequence ClassificationCode0
PARs: Predicate-based Association Rules for Efficient and Accurate Model-Agnostic Anomaly ExplanationCode0
Explainable Machine Learning for Cyberattack Identification from Traffic FlowsCode0
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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