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 2001–2050 of 4856 papers

TitleStatusHype
A Deep Look Into -- Automated Lung X-Ray Abnormality Detection System—0
Fusing Dictionary Learning and Support Vector Machines for Unsupervised Anomaly DetectionCode0
A Real-time Anomaly Detection Using Convolutional Autoencoder with Dynamic Threshold—0
Test Time Training for Industrial Anomaly Segmentation—0
Learning with errors based dynamic encryption that discloses residue signal for anomaly detection—0
Foundation Models for Structural Health MonitoringCode0
TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly DetectionCode0
Transfer learning applications for anomaly detection in wind turbines—0
Enhancing Functional Safety in Automotive AMS Circuits through Unsupervised Machine Learning—0
Decentralized Collaborative Learning Framework with External Privacy Leakage Analysis—0
Harnessing Large Language Models for Training-free Video Anomaly Detection—0
On the True Distribution Approximation of Minimum Bayes-Risk DecodingCode0
Attire-Based Anomaly Detection in Restricted Areas Using YOLOv8 for Enhanced CCTV Security—0
ADs: Active Data-sharing for Data Quality Assurance in Advanced Manufacturing Systems—0
Absolute-Unified Multi-Class Anomaly Detection via Class-Agnostic Distribution Alignment—0
MTMMC: A Large-Scale Real-World Multi-Modal Camera Tracking Benchmark—0
Long-Tailed Anomaly Detection with Learnable Class Names—0
Enhancing Anomaly Detection in Financial Markets with an LLM-based Multi-Agent Framework—0
Patch Spatio-Temporal Relation Prediction for Video Anomaly Detection—0
Cross-System Categorization of Abnormal Traces in Microservice-Based Systems via Meta-Learning—0
Temporal Graph Networks for Graph Anomaly Detection in Financial Networks—0
Dealing with Imbalanced Classes in Bot-IoT Dataset—0
Few-shot Online Anomaly Detection and SegmentationCode0
Road Obstacle Detection based on Unknown Objectness Scores—0
Practical Applications of Advanced Cloud Services and Generative AI Systems in Medical Image Analysis—0
AD-NEv++ : The multi-architecture neuroevolution-based multivariate anomaly detection framework—0
Constricting Normal Latent Space for Anomaly Detection with Normal-only Training Data—0
A task of anomaly detection for a smart satellite Internet of things system—0
Diffusion Models with Ensembled Structure-Based Anomaly Scoring for Unsupervised Anomaly DetectionCode0
Toward Multi-class Anomaly Detection: Exploring Class-aware Unified Model against Inter-class Interference—0
Triple Component Matrix Factorization: Untangling Global, Local, and Noisy Components—0
A Classifier-Based Approach to Multi-Class Anomaly Detection for Astronomical TransientsCode0
Machine Learning-based Layer-wise Detection of Overheating Anomaly in LPBF using Photodiode Data—0
DMAD: Dual Memory Bank for Real-World Anomaly DetectionCode0
Wildfire danger prediction optimization with transfer learningCode0
A Comparison of Deep Learning Architectures for Spacecraft Anomaly Detection—0
Improving Interpretability of Scores in Anomaly Detection Based on Gaussian-Bernoulli Restricted Boltzmann Machine—0
Unveiling the Anomalies in an Ever-Changing World: A Benchmark for Pixel-Level Anomaly Detection in Continual Learning—0
Out-of-Distribution Detection Should Use Conformal Prediction (and Vice-versa?)—0
Graph-Jigsaw Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection—0
Tokensome: Towards a Genetic Vision-Language GPT for Explainable and Cognitive Karyotyping—0
usfAD Based Effective Unknown Attack Detection Focused IDS Framework—0
Causality from Bottom to Top: A Survey—0
Anomaly Detection Based on Isolation Mechanisms: A Survey—0
DTOR: Decision Tree Outlier Regressor to explain anomaliesCode0
From Chaos to Clarity: Time Series Anomaly Detection in Astronomical ObservationsCode0
Generation is better than Modification: Combating High Class Homophily Variance in Graph Anomaly Detection—0
Single- and Multi-Agent Private Active Sensing: A Deep Neuroevolution Approach—0
Detecting Anomalies in Dynamic Graphs via Memory enhanced Normality—0
Explainable Machine Learning-Based Security and Privacy Protection Framework for Internet of Medical Things Systems—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