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 1381–1390 of 4856 papers

Title	Date	Tasks	Status
Application of advanced machine learning algorithms for anomaly detection and quantitative prediction in protein A chromatography	Sep 5, 2022	Anomaly DetectionDimensionality Reduction	—Unverified
Application Of ADNN For Background Subtraction In Smart Surveillance System	Dec 31, 2022	Anomaly DetectionMotion Detection	—Unverified
Appearance Blur-driven AutoEncoder and Motion-guided Memory Module for Video Anomaly Detection	Sep 26, 2024	Anomaly DetectionDomain Adaptation	—Unverified
A Poisson Process AutoDecoder for X-ray Sources	Feb 3, 2025	Anomaly DetectionDecoder	—Unverified
An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing	Jul 26, 2019	Anomaly DetectionDecoder	—Unverified
AD-NEV: A Scalable Multi-level Neuroevolution Framework for Multivariate Anomaly Detection	May 25, 2023	Anomaly DetectionModel Optimization	—Unverified
A Physics-Based Context-Aware Approach for Anomaly Detection in Teleoperated Driving Operations Under False Data Injection Attacks	Oct 17, 2024	Anomaly DetectionSteering Control	—Unverified
A Personalized Federated Learning Algorithm: an Application in Anomaly Detection	Nov 4, 2021	Anomaly DetectionFederated Learning	—Unverified
A Comprehensive Study of Machine Learning Techniques for Log-Based Anomaly Detection	Jul 31, 2023	Anomaly DetectionDeep Learning	—Unverified
APALU: A Trainable, Adaptive Activation Function for Deep Learning Networks	Feb 13, 2024	Anomaly DetectionDeep Learning	—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