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 3526–3550 of 4856 papers

Title	Date	Tasks	Status	Hype
An Explainable Artificial Intelligence Approach for Unsupervised Fault Detection and Diagnosis in Rotating Machinery	Feb 23, 2021	Anomaly DetectionBIG-bench Machine Learning	—Unverified	0
SliceNStitch: Continuous CP Decomposition of Sparse Tensor Streams	Feb 23, 2021	Anomaly DetectionRecommendation Systems	CodeCode Available	1
Unsupervised Brain Anomaly Detection and Segmentation with Transformers	Feb 23, 2021	Anomaly DetectionUnsupervised Anomaly Detection	—Unverified	0
Robust and Transferable Anomaly Detection in Log Data using Pre-Trained Language Models	Feb 23, 2021	Anomaly Detection	—Unverified	0
Few-shot Network Anomaly Detection via Cross-network Meta-learning	Feb 22, 2021	Anomaly DetectionFew-Shot Learning	CodeCode Available	1
Self-Taught Semi-Supervised Anomaly Detection on Upper Limb X-rays	Feb 19, 2021	Anomaly DetectionSelf-Supervised Anomaly Detection	CodeCode Available	0
Interpretable Stability Bounds for Spectral Graph Filters	Feb 18, 2021	Anomaly DetectionDenoising	—Unverified	0
Unsupervised Clustering of Time Series Signals using Neuromorphic Energy-Efficient Temporal Neural Networks	Feb 18, 2021	Anomaly DetectionClustering	—Unverified	0
Topological Obstructions to Autoencoding	Feb 16, 2021	Anomaly DetectionInductive Bias	—Unverified	0
Anomaly Detection for Scenario-based Insider Activities using CGAN Augmented Data	Feb 15, 2021	Anomaly DetectionGeneral Classification	—Unverified	0
Towards AIOps in Edge Computing Environments	Feb 12, 2021	Anomaly DetectionCloud Computing	—Unverified	0
How Far Should We Look Back to Achieve Effective Real-Time Time-Series Anomaly Detection?	Feb 12, 2021	Anomaly DetectionFraud Detection	—Unverified	0
LIME: Low-Cost and Incremental Learning for Dynamic Heterogeneous Information Networks	Feb 11, 2021	Anomaly DetectionFraud Detection	CodeCode Available	0
Anomaly Detection through Transfer Learning in Agriculture and Manufacturing IoT Systems	Feb 11, 2021	Anomaly DetectionTime Series Analysis	—Unverified	0
Mutually exciting point process graphs for modelling dynamic networks	Feb 11, 2021	Anomaly DetectionPoint Processes	CodeCode Available	0
On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions	Feb 10, 2021	Anomaly DetectionSafe Reinforcement Learning	—Unverified	0
Clustered Hierarchical Anomaly and Outlier Detection Algorithms	Feb 9, 2021	Anomaly DetectionClustering	CodeCode Available	1
Is Space-Time Attention All You Need for Video Understanding?	Feb 9, 2021	Action ClassificationAction Recognition	CodeCode Available	2
Negative Data Augmentation	Feb 9, 2021	Action RecognitionAnomaly Detection	CodeCode Available	1
VeeAlign: Multifaceted Context Representation using Dual Attention for Ontology Alignment	Feb 8, 2021	Anomaly DetectionData Integration	CodeCode Available	0
Exact Optimization of Conformal Predictors via Incremental and Decremental Learning	Feb 5, 2021	Anomaly Detectionregression	CodeCode Available	0
Graph Coding for Model Selection and Anomaly Detection in Gaussian Graphical Models	Feb 4, 2021	Anomaly DetectionModel Selection	—Unverified	0
SAFELearning: Enable Backdoor Detectability In Federated Learning With Secure Aggregation	Feb 4, 2021	Anomaly DetectionFederated Learning	—Unverified	0
Evaluation of Point Pattern Features for Anomaly Detection of Defect within Random Finite Set Framework	Feb 3, 2021	Anomaly DetectionDefect Detection	—Unverified	0
Anomaly Detection of Time Series with Smoothness-Inducing Sequential Variational Auto-Encoder	Feb 2, 2021	Anomaly DetectionDensity Estimation	—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	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