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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 951–1000 of 4856 papers

TitleStatusHype
Automatic Hyperparameter Tuning Method for Local Outlier Factor, with Applications to Anomaly DetectionCode0
Automatic Feature Extraction for Heartbeat Anomaly DetectionCode0
Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density EstimationCode0
Localizing Anomalies via Multiscale Score Matching AnalysisCode0
Localized Multiple Kernel Learning for Anomaly Detection: One-class ClassificationCode0
Locally Interpretable One-Class Anomaly Detection for Credit Card Fraud DetectionCode0
Link Analysis meets Ontologies: Are Embeddings the Answer?Code0
Lifelong Continual Learning for Anomaly Detection: New Challenges, Perspectives, and InsightsCode0
Lightning Fast Video Anomaly Detection via Adversarial Knowledge DistillationCode0
Local2Global: A distributed approach for scaling representation learning on graphsCode0
Leveraging Contaminated Datasets to Learn Clean-Data Distribution with Purified Generative Adversarial NetworksCode0
Less-supervised learning with knowledge distillation for sperm morphology analysisCode0
Leveraging Log Instructions in Log-based Anomaly DetectionCode0
Automated anomaly-aware 3D segmentation of bones and cartilages in knee MR images from the Osteoarthritis InitiativeCode0
Learn Suspected Anomalies from Event Prompts for Video Anomaly DetectionCode0
Leveraging the Mahalanobis Distance to enhance Unsupervised Brain MRI Anomaly DetectionCode0
Anomaly Detection by Recombining Gated Unsupervised ExpertsCode0
Learning Temporal Regularity in Video SequencesCode0
Lightweight Collaborative Anomaly Detection for the IoT using BlockchainCode0
LIME: Low-Cost and Incremental Learning for Dynamic Heterogeneous Information NetworksCode0
LR-IAD:Mask-Free Industrial Anomaly Detection with Logical ReasoningCode0
Localizing Anomalies in Critical Infrastructure using Model-Based Drift ExplanationsCode0
Automatic Anomaly Detection in the Cloud Via Statistical LearningCode0
Learning Regularity in Skeleton Trajectories for Anomaly Detection in VideosCode0
Autoencoders and Generative Adversarial Networks for Imbalanced Sequence ClassificationCode0
Generative Modeling by Inclusive Neural Random Fields with Applications in Image Generation and Anomaly DetectionCode0
Learning Neural Representations for Network Anomaly DetectionCode0
Learning Networks from Random Walk-Based Node SimilaritiesCode0
Learning normal asymmetry representations for homologous brain structuresCode0
Learning Representations for Time Series ClusteringCode0
Learning from Multiple Expert Annotators for Enhancing Anomaly Detection in Medical Image AnalysisCode0
Learning Front-end Filter-bank Parameters using Convolutional Neural Networks for Abnormal Heart Sound DetectionCode0
AURSAD: Universal Robot Screwdriving Anomaly Detection DatasetCode0
Learning Cortical Anomaly through Masked Encoding for Unsupervised Heterogeneity MappingCode0
A Uniform Framework for Anomaly Detection in Deep Neural NetworksCode0
Learning Deep Features for One-Class ClassificationCode0
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier DetectionCode0
Latent Space Autoregression for Novelty DetectionCode0
A Flexible Framework for Anomaly Detection via Dimensionality ReductionCode0
LEAN-DMKDE: Quantum Latent Density Estimation for Anomaly DetectionCode0
Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context LearningCode0
Large Models in Dialogue for Active Perception and Anomaly DetectionCode0
AFiRe: Anatomy-Driven Self-Supervised Learning for Fine-Grained Representation in Radiographic ImagesCode0
LSCP: Locally Selective Combination in Parallel Outlier EnsemblesCode0
Language-Assisted Feature Transformation for Anomaly DetectionCode0
Landmine Detection Using Autoencoders on Multi-polarization GPR Volumetric DataCode0
Known Unknowns: Uncertainty Quality in Bayesian Neural NetworksCode0
Audio-Visual Dataset and Method for Anomaly Detection in Traffic VideosCode0
KDSelector: A Knowledge-Enhanced and Data-Efficient Model Selector Learning Framework for Time Series Anomaly DetectionCode0
Kernel-Based Anomaly Detection Using Generalized Hyperbolic ProcessesCode0
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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