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 2401–2410 of 4856 papers

Title	Date	Tasks	Status
Anomaly Detection Models for IoT Time Series Data	Nov 30, 2018	Anomaly DetectionTime Series	—Unverified
High Dimensional Data Modeling Techniques for Detection of Chemical Plumes and Anomalies in Hyperspectral Images and Movies	Sep 24, 2015	Anomaly Detection	—Unverified
CNC: Cross-modal Normality Constraint for Unsupervised Multi-class Anomaly Detection	Dec 31, 2024	Anomaly DetectionAttribute	—Unverified
Higher-Order Moment-Based Anomaly Detection	Oct 30, 2020	Anomaly Detection	—Unverified
Higher-order Structure Based Anomaly Detection on Attributed Networks	Jun 7, 2024	Anomaly DetectionAttribute	—Unverified
Anomaly Detection of Command Shell Sessions based on DistilBERT: Unsupervised and Supervised Approaches	Oct 20, 2023	Anomaly DetectionComputer Security	—Unverified
A Light-weight and Unsupervised Method for Near Real-time Behavioral Analysis using Operational Data Measurement	Jan 10, 2024	Anomaly Detection	—Unverified
Hi-SAM: A high-scalable authentication model for satellite-ground Zero-Trust system using mean field game	Aug 12, 2024	Anomaly Detection	—Unverified
Graph Anomaly Detection in Time Series: A Survey	Jan 31, 2023	Anomaly DetectionGraph Anomaly Detection	—Unverified
Graph-Based Method for Anomaly Prediction in Brain Network	Apr 15, 2019	Anomaly DetectionFunctional Connectivity	—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