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 4226–4250 of 4856 papers

Title	Date	Tasks	Status	Hype
Transcriptional Response of SK-N-AS Cells to Methamidophos	Aug 11, 2019	Anomaly DetectionCausal Inference	—Unverified	0
ToyADMOS: A Dataset of Miniature-Machine Operating Sounds for Anomalous Sound Detection	Aug 9, 2019	Anomaly DetectionFault Diagnosis	CodeCode Available	1
What goes around comes around: Cycle-Consistency-based Short-Term Motion Prediction for Anomaly Detection using Generative Adversarial Networks	Aug 8, 2019	Anomaly DetectionGenerative Adversarial Network	—Unverified	0
Task-Oriented Optimal Sequencing of Visualization Charts	Aug 7, 2019	Anomaly DetectionReinforcement Learning	—Unverified	0
Abnormality Detection in Musculoskeletal Radiographs with Convolutional Neural Networks(Ensembles) and Performance Optimization	Aug 6, 2019	Anomaly DetectionDiagnostic	—Unverified	0
An Adaptive Anaphylaxis Detection and Emergency Response System	Aug 5, 2019	Anomaly Detection	CodeCode Available	0
Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain Shift	Aug 3, 2019	Anomaly DetectionDiversity	CodeCode Available	0
Developing an Unsupervised Real-time Anomaly Detection Scheme for Time Series with Multi-seasonality	Aug 3, 2019	Anomaly DetectionLine Detection	—Unverified	0
TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems	Aug 2, 2019	Anomaly Detection	CodeCode Available	0
Unsupervised Representation Learning and Anomaly Detection in ECG Sequences	Aug 1, 2019	Anomaly DetectionClustering	—Unverified	0
Learning Neural Representations for Network Anomaly Detection	Aug 1, 2019	Anomaly DetectionIntrusion Detection	CodeCode Available	0
MSNM-Sensor: An Applied Network Monitoring Tool for Anomaly Detection in Complex Networks and Systems	Jul 31, 2019	Anomaly DetectionEvent Detection	CodeCode Available	0
Q-MIND: Defeating Stealthy DoS Attacks in SDN with a Machine-learning based Defense Framework	Jul 27, 2019	Anomaly DetectionBIG-bench Machine Learning	—Unverified	0
An Encoder-Decoder Based Approach for Anomaly Detection with Application in Additive Manufacturing	Jul 26, 2019	Anomaly DetectionDecoder	—Unverified	0
Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network	Jul 25, 2019	Anomaly DetectionTime Series	CodeCode Available	0
Motion-Aware Feature for Improved Video Anomaly Detection	Jul 24, 2019	Action RecognitionAnomaly Detection	—Unverified	0
CAMLPAD: Cybersecurity Autonomous Machine Learning Platform for Anomaly Detection	Jul 23, 2019	Anomaly ClassificationAnomaly Detection	—Unverified	0
A Neural Network-Based On-device Learning Anomaly Detector for Edge Devices	Jul 23, 2019	Anomaly DetectionCPU	—Unverified	0
Early Anomaly Detection in Power Systems Based on Random Matrix Theory	Jul 21, 2019	Anomaly Detection	—Unverified	0
Spatio-Temporal Correlation Analysis of Online Monitoring Data for Anomaly Detection and Location in Distribution Networks	Jul 21, 2019	Anomaly Detection	—Unverified	0
Batch Uniformization for Minimizing Maximum Anomaly Score of DNN-based Anomaly Detection in Sounds	Jul 19, 2019	Anomaly DetectionDensity Estimation	—Unverified	0
An Adaptive Approach for Anomaly Detector Selection and Fine-Tuning in Time Series	Jul 18, 2019	Anomaly DetectionTime Series	—Unverified	0
Constrained Concealment Attacks against Reconstruction-based Anomaly Detectors in Industrial Control Systems	Jul 17, 2019	Anomaly Detection	CodeCode Available	1
The Tradeoff Between Privacy and Accuracy in Anomaly Detection Using Federated XGBoost	Jul 16, 2019	Anomaly DetectionFederated Learning	CodeCode Available	0
Exploring Deep Anomaly Detection Methods Based on Capsule Net	Jul 15, 2019	Anomaly DetectionPrediction	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