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 971–980 of 4856 papers

Title	Date	Tasks	Status
Automated visual inspection of CMS HGCAL silicon sensor surface using an ensemble of a deep convolutional autoencoder and classifier	Mar 9, 2023	Anomaly Detection	—Unverified
Anomaly Detection for a Water Treatment System Using Unsupervised Machine Learning	Sep 15, 2017	Anomaly DetectionBIG-bench Machine Learning	—Unverified
AdaFlow: Domain-Adaptive Density Estimator with Application to Anomaly Detection and Unpaired Cross-Domain Translation	Dec 14, 2018	Anomaly DetectionDensity Estimation	—Unverified
Automated, real-time hospital ICU emergency signaling: A field-level implementation	Nov 3, 2021	Anomaly Detection	—Unverified
Automated Real-time Anomaly Detection in Human Trajectories using Sequence to Sequence Networks	Jul 12, 2019	Anomaly DetectionTime Series	—Unverified
Automatic Clustering for Unsupervised Risk Diagnosis of Vehicle Driving for Smart Road	Nov 24, 2020	Anomaly DetectionBayesian Optimisation	—Unverified
Anomaly Detection for High-Dimensional Data Using Large Deviations Principle	Sep 28, 2021	Anomaly DetectionTime Series	—Unverified
Automatic Interaction and Activity Recognition from Videos of Human Manual Demonstrations with Application to Anomaly Detection	Apr 19, 2023	Activity RecognitionAnomaly Detection	—Unverified
Automatic Mapping of Anatomical Landmarks from Free-Text Using Large Language Models: Insights from Llama-2	Oct 16, 2024	Anomaly Detection	—Unverified
An Improved Anomaly Detection Model for Automated Inspection of Power Line Insulators	Nov 14, 2023	Anomaly DetectionFault Detection	—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	GLASS	Detection AUROC	99.9	—	Unverified
5	UniNet	Detection AUROC	99.9	—	Unverified
6	HETMM	Detection AUROC	99.8	—	Unverified
7	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	DDAD	Detection AUROC	99.8	—	Unverified
10	PBAS	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	INP-Former ViT-B (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
5	DDAD	Detection AUROC	98.9	—	Unverified
6	Dinomaly ViT-L (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