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 3141–3150 of 4856 papers

Title	Date	Tasks	Status	Hype
Minimal-Configuration Anomaly Detection for IIoT Sensors	Oct 8, 2021	Anomaly DetectionFeature Engineering	—Unverified	0
Anomaly Detection in Beehives: An Algorithm Comparison	Oct 8, 2021	Anomaly DetectionBIG-bench Machine Learning	—Unverified	0
AnoSeg: Anomaly Segmentation Network Using Self-Supervised Learning	Oct 7, 2021	Anomaly DetectionAnomaly Segmentation	—Unverified	0
Differential Anomaly Detection for Facial Images	Oct 7, 2021	Anomaly DetectionFace Recognition	—Unverified	0
Multivariate Anomaly Detection based on Prediction Intervals Constructed using Deep Learning	Oct 7, 2021	Anomaly DetectionDeep Learning	—Unverified	0
Generative Pre-Trained Transformer for Cardiac Abnormality Detection	Oct 7, 2021	Anomaly DetectionClassification	—Unverified	0
Tribuo: Machine Learning with Provenance in Java	Oct 6, 2021	Anomaly DetectionBIG-bench Machine Learning	CodeCode Available	2
A Uniform Framework for Anomaly Detection in Deep Neural Networks	Oct 6, 2021	Adversarial AttackAnomaly Detection	CodeCode Available	0
Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy	Oct 6, 2021	Anomaly DetectionTime Series	CodeCode Available	2
Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection	Oct 6, 2021	Anomaly DetectionDefect Detection	CodeCode Available	1

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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