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 2601–2610 of 4856 papers

Title	Date	Tasks	Status	Hype
Deep Autoencoders for Anomaly Detection in Textured Images using CW-SSIM	Aug 30, 2022	Anomaly DetectionSSIM	CodeCode Available	0
Positive Difference Distribution for Image Outlier Detection using Normalizing Flows and Contrastive Data	Aug 30, 2022	Anomaly DetectionOutlier Detection	—Unverified	0
Learning Informative Health Indicators Through Unsupervised Contrastive Learning	Aug 28, 2022	Anomaly DetectionContrastive Learning	—Unverified	0
RUAD: unsupervised anomaly detection in HPC systems	Aug 28, 2022	Anomaly DetectionClustering	—Unverified	0
Self-Calibrating Anomaly and Change Detection for Autonomous Inspection Robots	Aug 26, 2022	Anomaly DetectionChange Detection	—Unverified	0
Deep Learning-based ECG Classification on Raspberry PI using a Tensorflow Lite Model based on PTB-XL Dataset	Aug 25, 2022	Anomaly DetectionECG Classification	—Unverified	0
Towards an Awareness of Time Series Anomaly Detection Models' Adversarial Vulnerability	Aug 24, 2022	Anomaly DetectionTime Series	CodeCode Available	0
Combining AI and AM - Improving Approximate Matching through Transformer Networks	Aug 24, 2022	Anomaly Detection	CodeCode Available	0
ADMoE: Anomaly Detection with Mixture-of-Experts from Noisy Labels	Aug 24, 2022	Anomaly DetectionMixture-of-Experts	—Unverified	0
Q-Net: Query-Informed Few-Shot Medical Image Segmentation	Aug 24, 2022	Anomaly DetectionImage Segmentation	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	GLASS	Detection AUROC	99.9	—	Unverified
5	UniNet	Detection AUROC	99.9	—	Unverified
6	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
7	DDAD	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	PBAS	Detection AUROC	99.8	—	Unverified
10	HETMM	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	DDAD	Detection AUROC	98.9	—	Unverified
5	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
7	DiffusionAD	Detection AUROC	98.8	—	Unverified
8	GLASS	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