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 3471–3480 of 4856 papers

Title	Date	Tasks	Status
Adaptive Anomaly Detection for Internet of Things in Hierarchical Edge Computing: A Contextual-Bandit Approach	Aug 9, 2021	Anomaly DetectionEdge-computing	—Unverified
Ensemble neuroevolution based approach for multivariate time series anomaly detection	Aug 8, 2021	Anomaly DetectionDeep Learning	—Unverified
Locally Interpretable One-Class Anomaly Detection for Credit Card Fraud Detection	Aug 5, 2021	Anomaly DetectionData Augmentation	CodeCode Available
Using a Collated Cybersecurity Dataset for Machine Learning and Artificial Intelligence	Aug 5, 2021	Anomaly DetectionBIG-bench Machine Learning	—Unverified
Deep Anomaly Discovery From Unlabeled Videos via Normality Advantage and Self-Paced Refinement	Aug 4, 2021	Anomaly DetectionVideo Anomaly Detection	—Unverified
Unsupervised Detection of Lung Nodules in Chest Radiography Using Generative Adversarial Networks	Aug 4, 2021	Anomaly DetectionDecoder	—Unverified
HTTP2vec: Embedding of HTTP Requests for Detection of Anomalous Traffic	Aug 3, 2021	Anomaly DetectionIntrusion Detection	—Unverified
Efficacy of Statistical and Artificial Intelligence-based False Information Cyberattack Detection Models for Connected Vehicles	Aug 2, 2021	Anomaly Detection	—Unverified
HR-Crime: Human-Related Anomaly Detection in Surveillance Videos	Jul 31, 2021	Anomaly DetectionAnomaly Detection In Surveillance Videos	—Unverified
Margin-Aware Intra-Class Novelty Identification for Medical Images	Jul 31, 2021	Anomaly DetectionMedical Image Analysis	CodeCode Available

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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