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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 2491–2500 of 4856 papers

Title	Date	Tasks	Status
Artificial Intelligence and Machine Learning in 5G Network Security: Opportunities, advantages, and future research trends	Jul 9, 2020	Anomaly DetectionBIG-bench Machine Learning	—Unverified
Artificial intelligence for abnormality detection in high volume neuroimaging: a systematic review and meta-analysis	May 9, 2024	Anomaly DetectionDiagnostic	—Unverified
A Scalable Algorithm for Anomaly Detection via Learning-Based Controlled Sensing	May 12, 2021	Anomaly DetectionDecision Making	—Unverified
A Scalable and Generalized Deep Learning Framework for Anomaly Detection in Surveillance Videos	Jul 17, 2024	Anomaly DetectionAnomaly Detection In Surveillance Videos	—Unverified
A Scalable Approach for Outlier Detection in Edge Streams Using Sketch-based Approximations	May 7, 2016	Anomaly DetectionAnomaly Detection in Edge Streams	—Unverified
A scalable framework for annotating photovoltaic cell defects in electroluminescence images	Dec 15, 2022	Anomaly DetectionAnomaly Segmentation	—Unverified
A Scalable k-Medoids Clustering via Whale Optimization Algorithm	Aug 30, 2024	Anomaly DetectionClustering	—Unverified
ASE: Anomaly Scoring Based Ensemble Learning for Imbalanced Datasets	Mar 21, 2022	Anomaly DetectionBinary Classification	—Unverified
A secondary immune response based on co-evolutive populations of agents for anomaly detection and characterization	Sep 11, 2021	Anomaly DetectionSpecificity	—Unverified
A Self-Commissioning Edge Computing Method for Data-Driven Anomaly Detection in Power Electronic Systems	Dec 5, 2023	Anomaly DetectionDiversity	—Unverified

Show:10 25 50

← PrevPage 250 of 486Next →

All datasets MVTec AD VisA MVTec LOCO AD One-class CIFAR-10 CUHK Avenue ShanghaiTech Fishyscapes L&F UCR Anomaly Archive MPDD BTAD One-class CIFAR-100 UBnormal

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	CPR-faster(TensorRT)	FPS	1,016	—	Unverified
2	CPR-fast(TensorRT)	FPS	362	—	Unverified
3	CPR(TensorRT)	FPS	130	—	Unverified
4	UniNet	Detection AUROC	99.9	—	Unverified
5	GLASS	Detection AUROC	99.9	—	Unverified
6	PBAS	Detection AUROC	99.8	—	Unverified
7	HETMM	Detection AUROC	99.8	—	Unverified
8	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UniNet	Detection AUROC	99.8	—	Unverified
2	GLAD	Detection AUROC	99.5	—	Unverified
3	UniNet(model-unified multi-class)	Detection AUROC	99.15	—	Unverified
4	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	DDAD	Detection AUROC	98.9	—	Unverified
7	GLASS	Detection AUROC	98.8	—	Unverified
8	DiffusionAD	Detection AUROC	98.8	—	Unverified
9	TransFusion	Detection AUROC	98.7	—	Unverified
10	HETMM	Detection AUROC	98.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CSAD	Avg. Detection AUROC	95.3	—	Unverified
2	PSAD	Avg. Detection AUROC	94.9	—	Unverified