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

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Showing 2861–2870 of 4856 papers

Title	Date	Tasks	Status
Privacy-Preserving Anomaly Detection in Stochastic Dynamical Systems: Synthesis of Optimal Gaussian Mechanisms	Nov 7, 2022	Anomaly DetectionPrivacy Preserving	—Unverified
Degradation Prediction of Semiconductor Lasers using Conditional Variational Autoencoder	Nov 5, 2022	Anomaly DetectionPrediction	—Unverified
A Machine Learning-based Framework for Predictive Maintenance of Semiconductor Laser for Optical Communication	Nov 5, 2022	Anomaly DetectionDecision Making	—Unverified
Deep learning for structural health monitoring: An application to heritage structures	Nov 4, 2022	Anomaly DetectionStructural Health Monitoring	—Unverified
Discussion of Features for Acoustic Anomaly Detection under Industrial Disturbing Noise in an End-of-Line Test of Geared Motors	Nov 3, 2022	Anomaly DetectionDiversity	—Unverified
Generation of Anonymous Chest Radiographs Using Latent Diffusion Models for Training Thoracic Abnormality Classification Systems	Nov 2, 2022	Anomaly DetectionImage Generation	—Unverified
DyAnNet: A Scene Dynamicity Guided Self-Trained Video Anomaly Detection Network	Nov 2, 2022	Anomaly DetectionVideo Anomaly Detection	—Unverified
Exploiting Spatial-temporal Correlations for Video Anomaly Detection	Nov 2, 2022	Anomaly DetectionDiversity	—Unverified
HFN: Heterogeneous Feature Network for Multivariate Time Series Anomaly Detection	Nov 1, 2022	Anomaly DetectionGraph structure learning	—Unverified
Unsupervised Anomaly Detection of Paranasal Anomalies in the Maxillary Sinus	Nov 1, 2022	Anomaly DetectionUnsupervised Anomaly 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	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