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 2101–2110 of 4856 papers

Title	Date	Tasks	Status	Hype
SLSG: Industrial Image Anomaly Detection by Learning Better Feature Embeddings and One-Class Classification	Apr 30, 2023	Anomaly DetectionClassification	—Unverified	0
POET: A Self-learning Framework for PROFINET Industrial Operations Behaviour	Apr 29, 2023	Anomaly DetectionIntrusion Detection	—Unverified	0
Model-Based Monitoring and State Estimation for Digital Twins: The Kalman Filter	Apr 29, 2023	Anomaly DetectionFault Detection	—Unverified	0
Synthetic Aperture Anomaly Imaging	Apr 26, 2023	Anomaly Detection	—Unverified	0
Real-time Safety Assessment of Dynamic Systems in Non-stationary Environments: A Review of Methods and Techniques	Apr 25, 2023	Active LearningAnomaly Detection	CodeCode Available	0
Blockchain Large Language Models	Apr 25, 2023	Anomaly DetectionIntrusion Detection	—Unverified	0
MoniLog: An Automated Log-Based Anomaly Detection System for Cloud Computing Infrastructures	Apr 24, 2023	Anomaly DetectionCloud Computing	—Unverified	0
Detecting Socially Abnormal Highway Driving Behaviors via Recurrent Graph Attention Networks	Apr 23, 2023	Anomaly DetectionGraph Attention	CodeCode Available	1
Constructing a meta-learner for unsupervised anomaly detection	Apr 22, 2023	Anomaly DetectionAutoML	—Unverified	0
Reconstruction-based LSTM-Autoencoder for Anomaly-based DDoS Attack Detection over Multivariate Time-Series Data	Apr 21, 2023	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	GLASS	Detection AUROC	99.9	—	Unverified
5	UniNet	Detection AUROC	99.9	—	Unverified
6	INP-Fomer ViT-L (model-unified multi-class)	Detection AUROC	99.8	—	Unverified
7	DDAD	Detection AUROC	99.8	—	Unverified
8	EfficientAD (early stopping)	Detection AUROC	99.8	—	Unverified
9	PBAS	Detection AUROC	99.8	—	Unverified
10	HETMM	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	DDAD	Detection AUROC	98.9	—	Unverified
5	Dinomaly ViT-L (model-unified multi-class)	Detection AUROC	98.9	—	Unverified
6	INP-Former ViT-B (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