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 1931–1940 of 4856 papers

Title	Date	Tasks	Status
Federated Anomaly Detection over Distributed Data Streams	May 16, 2022	Anomaly DetectionFederated Learning	—Unverified
Automated Anomaly Detection on European XFEL Klystrons	May 20, 2024	Anomaly DetectionDimensionality Reduction	—Unverified
Evaluating the Capabilities of Multi-modal Reasoning Models with Synthetic Task Data	Jun 1, 2023	Anomaly DetectionImage Generation	—Unverified
Evaluating the Effectiveness of Video Anomaly Detection in the Wild: Online Learning and Inference for Real-world Deployment	Apr 29, 2024	Anomaly DetectionVideo Anomaly Detection	—Unverified
Automated Model Selection for Time-Series Anomaly Detection	Aug 25, 2020	Anomaly Detectionmodel	—Unverified
Anomaly Detection for an E-commerce Pricing System	Feb 25, 2019	Anomaly DetectionModel Selection	—Unverified
Evaluation of a Dual Convolutional Neural Network Architecture for Object-wise Anomaly Detection in Cluttered X-ray Security Imagery	Apr 10, 2019	Anomaly DetectionGeneral Classification	—Unverified
Evaluation of an Anomaly Detector for Routers using Parameterizable Malware in an IoT Ecosystem	Oct 29, 2021	Anomaly Detection	—Unverified
Evaluation of Color Anomaly Detection in Multispectral Images For Synthetic Aperture Sensing	Nov 8, 2022	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified
An Adaptive Event-based Data Converter for Always-on Biomedical Applications at the Edge	Nov 23, 2022	Anomaly Detection	—Unverified

Show:10 25 50

← PrevPage 194 of 486Next →

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