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 1771–1780 of 4856 papers

Title	Date	Tasks	Status
Anomaly Generation using Generative Adversarial Networks in Host Based Intrusion Detection	Dec 11, 2018	Anomaly DetectionIntrusion Detection	—Unverified
Analytical Discovery of Manifold with Machine Learning	Apr 3, 2025	Anomaly DetectionComputational Efficiency	—Unverified
CyberSentinel: An Emergent Threat Detection System for AI Security	Feb 20, 2025	Anomaly Detection	—Unverified
Cybersecurity threat detection based on a UEBA framework using Deep Autoencoders	May 14, 2025	Anomaly Detection	—Unverified
Evaluating the Capabilities of Multi-modal Reasoning Models with Synthetic Task Data	Jun 1, 2023	Anomaly DetectionImage Generation	—Unverified
Anomaly detection with Wasserstein GAN	Dec 6, 2018	Anomaly DetectionTime Series	—Unverified
Dynamic Interactional And Cooperative Network For Shield Machine	Nov 17, 2022	Anomaly Detection	—Unverified
CyberForce: A Federated Reinforcement Learning Framework for Malware Mitigation	Aug 11, 2023	Anomaly DetectionData Poisoning	—Unverified
A Systematic Review of Machine Learning in Sports Betting: Techniques, Challenges, and Future Directions	Oct 28, 2024	Anomaly DetectionFairness	—Unverified
Analysis of Vision-based Abnormal Red Blood Cell Classification	Jun 1, 2021	Anomaly DetectionBIG-bench Machine 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