SOTAVerified

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

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Showing 1401–1425 of 4856 papers

TitleStatusHype
Detecting Gait Abnormalities in Foot-Floor Contacts During Walking Through Footstep-Induced Structural Vibrations—0
Building an Efficient Intrusion Detection System Based on Feature Selection and Ensemble Classifier—0
An Efficient Approach for Anomaly Detection in Traffic Videos—0
An unsupervised approach towards promptable defect segmentation in laser-based additive manufacturing by Segment Anything—0
An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework—0
CyberCScope: Mining Skewed Tensor Streams and Online Anomaly Detection in Cybersecurity Systems—0
Anticipated Network Surveillance -- An extrapolated study to predict cyber-attacks using Machine Learning and Data Analytics—0
An Efficient Anomaly Detection Approach using Cube Sampling with Streaming Data—0
A comprehensive study of sparse codes on abnormality detection—0
Detecting Faults during Automatic Screwdriving: A Dataset and Use Case of Anomaly Detection for Automatic Screwdriving—0
Detecting Log Anomalies with Multi-Head Attention (LAMA)—0
Detecting out-of-context objects using contextual cues—0
Detecting Crypto Pump-and-Dump Schemes: A Thresholding-Based Approach to Handling Market Noise—0
An Autonomous Drone Swarm for Detecting and Tracking Anomalies among Dense Vegetation—0
Detecting Cyberattacks in Industrial Control Systems Using Convolutional Neural Networks—0
A Novel Representation of Periodic Pattern and Its Application to Untrained Anomaly Detection—0
An Automated Machine Learning Approach for Detecting Anomalous Peak Patterns in Time Series Data from a Research Watershed in the Northeastern United States Critical Zone—0
A Discriminative Framework for Anomaly Detection in Large Videos—0
Detecting Disengagement in Virtual Learning as an Anomaly using Temporal Convolutional Network Autoencoder—0
A Novel Data Pre-processing Technique: Making Data Mining Robust to Different Units and Scales of Measurement—0
An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction—0
A novel data-driven algorithm to predict anomalous prescription based on patient's feature set—0
An Automated Data Engineering Pipeline for Anomaly Detection of IoT Sensor Data—0
A Comprehensive Augmentation Framework for Anomaly Detection—0
Detecting Driver Drowsiness as an Anomaly Using LSTM Autoencoders—0
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All datasetsMVTec ADVisAMVTec LOCO ADOne-class CIFAR-10CUHK AvenueShanghaiTechFishyscapes L&FUCR Anomaly ArchiveMPDDBTADOne-class CIFAR-100UBnormal

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016—Unverified
2CPR-fast(TensorRT)FPS362—Unverified
3CPR(TensorRT)FPS130—Unverified
4GLASSDetection AUROC99.9—Unverified
5UniNetDetection AUROC99.9—Unverified
6HETMMDetection AUROC99.8—Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8—Unverified
8EfficientAD (early stopping)Detection AUROC99.8—Unverified
9DDADDetection AUROC99.8—Unverified
10PBASDetection AUROC99.8—Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8—Unverified
2GLADDetection AUROC99.5—Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15—Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9—Unverified
5DDADDetection AUROC98.9—Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9—Unverified
7DiffusionADDetection AUROC98.8—Unverified
8GLASSDetection AUROC98.8—Unverified
9TransFusionDetection AUROC98.7—Unverified
10HETMMDetection AUROC98.1—Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3—Unverified
2PSADAvg. Detection AUROC94.9—Unverified