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 2841–2850 of 4856 papers

Title	Date	Tasks	Status	Hype
Federated Learning for Distributed Spectrum Sensing in NextG Communication Networks	Apr 6, 2022	Anomaly DetectionFederated Learning	—Unverified	0
Learning to Adapt to Domain Shifts with Few-shot Samples in Anomalous Sound Detection	Apr 5, 2022	Anomaly DetectionDensity Estimation	—Unverified	0
A Survey on Graph Representation Learning Methods	Apr 4, 2022	Anomaly DetectionGraph Embedding	—Unverified	0
Distributed Anomaly Detection and Estimation over Sensor Networks: Observational-Equivalence and Q-Redundant Observer Design	Apr 4, 2022	Anomaly Detection	—Unverified	0
Do Deep Neural Networks Contribute to Multivariate Time Series Anomaly Detection?	Apr 4, 2022	Anomaly DetectionArticles	—Unverified	0
SAM-kNN Regressor for Online Learning in Water Distribution Networks	Apr 4, 2022	Anomaly Detection	CodeCode Available	0
Proactive Anomaly Detection for Robot Navigation with Multi-Sensor Fusion	Apr 3, 2022	Anomaly DetectionRobot Navigation	CodeCode Available	1
Quadratic Neuron-empowered Heterogeneous Autoencoder for Unsupervised Anomaly Detection	Apr 2, 2022	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	0
LEAD1.0: A Large-scale Annotated Dataset for Energy Anomaly Detection in Commercial Buildings	Mar 30, 2022	Anomaly DetectionTime Series	CodeCode Available	1
IGRF-RFE: A Hybrid Feature Selection Method for MLP-based Network Intrusion Detection on UNSW-NB15 Dataset	Mar 30, 2022	Anomaly Detectionfeature selection	—Unverified	0

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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