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 1031–1040 of 4856 papers

Title	Date	Tasks	Status	Hype
F2PAD: A General Optimization Framework for Feature-Level to Pixel-Level Anomaly Detection	Jul 9, 2024	Anomaly DetectionAnomaly Localization	—Unverified	0
Comparison of Optimizers for Fault Isolation and Diagnostics of Control Rod Drives	Jul 9, 2024	Anomaly DetectionDecoder	—Unverified	0
Ensembled Cold-Diffusion Restorations for Unsupervised Anomaly Detection	Jul 9, 2024	Anomaly DetectionUnsupervised Anomaly Detection	CodeCode Available	0
PSPU: Enhanced Positive and Unlabeled Learning by Leveraging Pseudo Supervision	Jul 9, 2024	Anomaly DetectionBinary Classification	—Unverified	0
TeVAE: A Variational Autoencoder Approach for Discrete Online Anomaly Detection in Variable-state Multivariate Time-series Data	Jul 9, 2024	Anomaly DetectionTime Series	CodeCode Available	0
Integrating Ontology Design with the CRISP-DM in the context of Cyber-Physical Systems Maintenance	Jul 9, 2024	Anomaly Detection	—Unverified	0
Explainable Differential Privacy-Hyperdimensional Computing for Balancing Privacy and Transparency in Additive Manufacturing Monitoring	Jul 9, 2024	Anomaly DetectionDefect Detection	CodeCode Available	0
neuralGAM: Explainable generalized additive neural networks with independent neural network training	Jul 8, 2024	Additive modelsAnomaly Detection	CodeCode Available	0
ORAN-Bench-13K: An Open Source Benchmark for Assessing LLMs in Open Radio Access Networks	Jul 8, 2024	Anomaly DetectionCode Generation	CodeCode Available	1
Deep Learning-based Anomaly Detection and Log Analysis for Computer Networks	Jul 8, 2024	Anomaly DetectionGenerative Adversarial Network	—Unverified	0

Show:10 25 50

← PrevPage 104 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