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 2591–2600 of 4856 papers

Title	Date	Tasks	Status	Hype
Application of advanced machine learning algorithms for anomaly detection and quantitative prediction in protein A chromatography	Sep 5, 2022	Anomaly DetectionDimensionality Reduction	—Unverified	0
RX-ADS: Interpretable Anomaly Detection using Adversarial ML for Electric Vehicle CAN data	Sep 5, 2022	Anomaly DetectionExplanation Generation	—Unverified	0
ADTR: Anomaly Detection Transformer with Feature Reconstruction	Sep 5, 2022	Anomaly Detection	—Unverified	0
HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human Disease	Sep 5, 2022	Anomaly DetectionDiagnostic	CodeCode Available	1
Quickest Anomaly Detection in Sensor Networks With Unlabeled Samples	Sep 4, 2022	Anomaly Detection	—Unverified	0
Neuromorphic implementation of ECG anomaly detection using delay chains	Sep 2, 2022	Anomaly Detection	—Unverified	0
nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation Methods	Sep 2, 2022	Anomaly DetectionBenchmarking	CodeCode Available	1
Deep Anomaly Detection and Search via Reinforcement Learning	Aug 31, 2022	Anomaly DetectionEnsemble Learning	—Unverified	0
RecLight: A Recurrent Neural Network Accelerator with Integrated Silicon Photonics	Aug 31, 2022	Activity RecognitionAnomaly Detection	—Unverified	0
Denoising Architecture for Unsupervised Anomaly Detection in Time-Series	Aug 30, 2022	Anomaly DetectionDecoder	CodeCode Available	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	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