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 3191–3200 of 4856 papers

Title	Date	Tasks	Status
LesionPaste: One-Shot Anomaly Detection for Medical Images	Mar 12, 2022	Anomaly DetectionMedical Image Analysis	—Unverified
Multiple Inputs Neural Networks for Medicare fraud Detection	Mar 11, 2022	Anomaly DetectionFraud Detection	—Unverified
A Review of Open Source Software Tools for Time Series Analysis	Mar 10, 2022	Anomaly DetectionTime Series	—Unverified
TiSAT: Time Series Anomaly Transformer	Mar 10, 2022	Anomaly DetectionTime Series	CodeCode Available
Machine Learning in NextG Networks via Generative Adversarial Networks	Mar 9, 2022	Anomaly DetectionBIG-bench Machine Learning	—Unverified
Anomaly Detection for Unmanned Aerial Vehicle Sensor Data Using a Stacked Recurrent Autoencoder Method with Dynamic Thresholding	Mar 9, 2022	Anomaly DetectionFault Detection	—Unverified
Transfer Learning as an Essential Tool for Digital Twins in Renewable Energy Systems	Mar 9, 2022	Anomaly DetectionTransfer Learning	—Unverified
Visual anomaly detection in video by variational autoencoder	Mar 8, 2022	Anomaly DetectionSelf-Driving Cars	—Unverified
Generative Cooperative Learning for Unsupervised Video Anomaly Detection	Mar 8, 2022	Anomaly DetectionOne-Class Classification	—Unverified
Battery Cloud with Advanced Algorithms	Mar 7, 2022	Anomaly DetectionManagement	—Unverified

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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