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 1651–1700 of 4856 papers

TitleStatusHype
PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communities—0
Constraint Guided AutoEncoders for Joint Optimization of Condition Indicator Estimation and Anomaly Detection in Machine Condition Monitoring—0
Fair Anomaly Detection For Imbalanced Groups—0
Unsupervised Hybrid framework for ANomaly Detection (HAND) -- applied to Screening MammogramCode0
Adaptive Anomaly Detection in Network Flows with Low-Rank Tensor Decompositions and Deep UnrollingCode0
Multimodal Attention-Enhanced Feature Fusion-based Weekly Supervised Anomaly Violence Detection—0
Enhancing Anomaly Detection via Generating Diversified and Hard-to-distinguish Synthetic Anomalies—0
Towards Multi-view Graph Anomaly Detection with Similarity-Guided Contrastive Clustering—0
Abnormal Event Detection In Videos Using Deep Embedding—0
OML-AD: Online Machine Learning for Anomaly Detection in Time Series DataCode0
Matrix Profile for Anomaly Detection on Multidimensional Time Series—0
Optimal Classification-based Anomaly Detection with Neural Networks: Theory and PracticeCode0
A Survey of Anomaly Detection in In-Vehicle Networks—0
A Continual and Incremental Learning Approach for TinyML On-device Training Using Dataset Distillation and Model Size Adaption—0
Ensemble Methods for Sequence Classification with Hidden Markov Models—0
Atom dimension adaptation for infinite set dictionary learning—0
GeMuCo: Generalized Multisensory Correlational Model for Body Schema Learning—0
Texture-AD: An Anomaly Detection Dataset and Benchmark for Real Algorithm Development—0
Context Enhancement with Reconstruction as Sequence for Unified Unsupervised Anomaly DetectionCode0
GDFlow: Anomaly Detection with NCDE-based Normalizing Flow for Advanced Driver Assistance System—0
Deep Learning for Video Anomaly Detection: A Review—0
A Novel Representation of Periodic Pattern and Its Application to Untrained Anomaly Detection—0
Memoryless Multimodal Anomaly Detection via Student-Teacher Network and Signed Distance Learning—0
Adapted-MoE: Mixture of Experts with Test-Time Adaption for Anomaly Detection—0
Anomaly Detection for Real-World Cyber-Physical Security using Quantum Hybrid Support Vector Machines—0
2DSig-Detect: a semi-supervised framework for anomaly detection on image data using 2D-signatures—0
Lung-DETR: Deformable Detection Transformer for Sparse Lung Nodule Anomaly Detection—0
Reducing Events to Augment Log-based Anomaly Detection Models: An Empirical Study—0
The role of data embedding in quantum autoencoders for improved anomaly detectionCode0
Unveiling Context-Related Anomalies: Knowledge Graph Empowered Decoupling of Scene and Action for Human-Related Video Anomaly Detection—0
A Dual-Path Framework with Frequency-and-Time Excited Network for Anomalous Sound Detection—0
Unsupervised Anomaly Detection and Localization with Generative Adversarial Networks—0
SDOoop: Capturing Periodical Patterns and Out-of-phase Anomalies in Streaming Data AnalysisCode0
Oddballness: universal anomaly detection with language models—0
NUMOSIM: A Synthetic Mobility Dataset with Anomaly Detection Benchmarks—0
Activity-Guided Industrial Anomalous Sound Detection against Interferences—0
TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model—0
Improving Robustness of Spectrogram Classifiers with Neural Stochastic Differential Equations—0
Interpreting Outliers in Time Series Data through Decoding Autoencoder—0
AutoEncoder Convolutional Neural Network for Pneumonia Detection—0
The Role of Transformer Models in Advancing Blockchain Technology: A Systematic Survey—0
A Scalable k-Medoids Clustering via Whale Optimization Algorithm—0
Graph neural network-based lithium-ion battery state of health estimation using partial discharging curve—0
Quantum Machine Learning for Anomaly Detection in Consumer Electronics—0
Real-Time Energy Pricing in New Zealand: An Evolving Stream AnalysisCode0
Multitask learning for improved scour detection: A dynamic wave tank studyCode0
Data Quality Monitoring through Transfer Learning on Anomaly Detection for the Hadron Calorimeters—0
Uni-3DAD: GAN-Inversion Aided Universal 3D Anomaly Detection on Model-free Products—0
HLogformer: A Hierarchical Transformer for Representing Log Data—0
ANVIL: Anomaly-based Vulnerability Identification without Labelled Training Data—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