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 2551–2600 of 4856 papers

TitleStatusHype
A Robust and Explainable Data-Driven Anomaly Detection Approach For Power Electronics—0
Self-supervised Learning for Clustering of Wireless Spectrum ActivityCode0
Anomaly Detection on Financial Time Series by Principal Component Analysis and Neural NetworksCode0
Challenges in Visual Anomaly Detection for Mobile RobotsCode1
Query-based Industrial Analytics over Knowledge Graphs with Ontology Reshaping—0
Oracle Analysis of Representations for Deep Open Set Detection—0
Hybrid AI-based Anomaly Detection Model using Phasor Measurement Unit Data—0
Contrastive Learning for Time Series on Dynamic Graphs—0
Deep Learning based pipeline for anomaly detection and quality enhancement in industrial binder jetting processes—0
Benchmarking energy consumption and latency for neuromorphic computing in condensed matter and particle physics—0
Improving Generalizability of Graph Anomaly Detection Models via Data AugmentationCode1
Learning Acceptance Regions for Many Classes with Anomaly Detection—0
An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile RobotsCode1
Collaborative Anomaly Detection—0
Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model—0
Infrared: A Meta Bug Detector—0
LogGD:Detecting Anomalies from System Logs by Graph Neural Networks—0
An Attention-guided Multistream Feature Fusion Network for Localization of Risky Objects in Driving VideosCode1
Anomaly Detection in Automatic Generation Control Systems Based on Traffic Pattern Analysis and Deep Transfer Learning—0
IoT Data Analytics in Dynamic Environments: From An Automated Machine Learning PerspectiveCode2
Self-Supervised Texture Image Anomaly Detection By Fusing Normalizing Flow and Dictionary Learning—0
Analytics and Machine Learning Powered Wireless Network Optimization and Planning—0
A Temporal Anomaly Detection System for Vehicles utilizing Functional Working Groups and Sensor Channels—0
TrADe Re-ID -- Live Person Re-Identification using Tracking and Anomaly DetectionCode0
Real-world Video Anomaly Detection by Extracting Salient Features in Videos—0
Deep Feature Selection for Anomaly Detection Based on Pretrained Network and Gaussian Discriminative AnalysisCode1
Hyperbolic Self-supervised Contrastive Learning Based Network Anomaly Detection—0
Detecting Driver Drowsiness as an Anomaly Using LSTM Autoencoders—0
Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamese—0
Deep Baseline Network for Time Series Modeling and Anomaly Detection—0
A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis—0
Activity report analysis with automatic single or multispan answer extraction—0
Fine-grain Inference on Out-of-Distribution Data with Hierarchical Classification—0
Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces—0
Anomaly Detection through Unsupervised Federated LearningCode0
Suspicious and Anomaly Detection—0
ReX: A Framework for Incorporating Temporal Information in Model-Agnostic Local Explanation Techniques—0
W-Transformers : A Wavelet-based Transformer Framework for Univariate Time Series ForecastingCode1
Context Recovery and Knowledge Retrieval: A Novel Two-Stream Framework for Video Anomaly DetectionCode0
Morphology-preserving Autoregressive 3D Generative Modelling of the BrainCode1
Application of advanced machine learning algorithms for anomaly detection and quantitative prediction in protein A chromatography—0
RX-ADS: Interpretable Anomaly Detection using Adversarial ML for Electric Vehicle CAN data—0
ADTR: Anomaly Detection Transformer with Feature Reconstruction—0
HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human DiseaseCode1
Quickest Anomaly Detection in Sensor Networks With Unlabeled Samples—0
Neuromorphic implementation of ECG anomaly detection using delay chains—0
nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation MethodsCode1
Deep Anomaly Detection and Search via Reinforcement Learning—0
RecLight: A Recurrent Neural Network Accelerator with Integrated Silicon Photonics—0
Denoising Architecture for Unsupervised Anomaly Detection in Time-SeriesCode0
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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