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 1871–1880 of 4856 papers

Title	Date	Tasks	Status
Custom DNN using Reward Modulated Inverted STDP Learning for Temporal Pattern Recognition	Jul 15, 2023	Anomaly DetectionKeyword Spotting	—Unverified
Enhanced Anomaly Detection in IoMT Networks using Ensemble AI Models on the CICIoMT2024 Dataset	Feb 17, 2025	Anomaly Detection	—Unverified
A Unified Framework for Context-Aware IoT Management and State-of-the-Art IoT Traffic Anomaly Detection	Dec 19, 2024	Anomaly DetectionManagement	—Unverified
Enhanced Cyber-Physical Security through Deep Learning Techniques	Aug 23, 2019	Anomaly DetectionDeep Learning	—Unverified
Enhanced Cyber-Physical Security Using Attack-resistant Cyber Nodes and Event-triggered Moving Target Defence	Oct 27, 2020	Anomaly Detection	—Unverified
Enhanced Federated Anomaly Detection Through Autoencoders Using Summary Statistics-Based Thresholding	Oct 11, 2024	Anomaly DetectionFederated Learning	—Unverified
Anomaly Detection with Tensor Networks	Jun 3, 2020	Anomaly DetectionComputational Efficiency	—Unverified
Enhanced Real-Time Threat Detection in 5G Networks: A Self-Attention RNN Autoencoder Approach for Spectral Intrusion Analysis	Nov 5, 2024	Anomaly DetectionComputational Efficiency	—Unverified
Enhanced semi-supervised stamping process monitoring with physically-informed feature extraction	Apr 30, 2025	Anomaly DetectionSemi-supervised Anomaly Detection	—Unverified
CurvGAD: Leveraging Curvature for Enhanced Graph Anomaly Detection	Feb 12, 2025	Anomaly DetectionAttribute	—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