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 2951–3000 of 4856 papers

TitleStatusHype
Real-world Video Anomaly Detection by Extracting Salient Features in Videos—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
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
A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis—0
Deep Baseline Network for Time Series Modeling and Anomaly Detection—0
Activity report analysis with automatic single or multispan answer extraction—0
Explanation Method for Anomaly Detection on Mixed Numerical and Categorical Spaces—0
Fine-grain Inference on Out-of-Distribution Data with Hierarchical Classification—0
Anomaly Detection through Unsupervised Federated LearningCode0
ReX: A Framework for Incorporating Temporal Information in Model-Agnostic Local Explanation Techniques—0
Suspicious and Anomaly Detection—0
Context Recovery and Knowledge Retrieval: A Novel Two-Stream Framework for Video Anomaly DetectionCode0
RX-ADS: Interpretable Anomaly Detection using Adversarial ML for Electric Vehicle CAN data—0
ADTR: Anomaly Detection Transformer with Feature Reconstruction—0
Application of advanced machine learning algorithms for anomaly detection and quantitative prediction in protein A chromatography—0
Quickest Anomaly Detection in Sensor Networks With Unlabeled Samples—0
Neuromorphic implementation of ECG anomaly detection using delay chains—0
RecLight: A Recurrent Neural Network Accelerator with Integrated Silicon Photonics—0
Deep Anomaly Detection and Search via Reinforcement Learning—0
Deep Autoencoders for Anomaly Detection in Textured Images using CW-SSIMCode0
Denoising Architecture for Unsupervised Anomaly Detection in Time-SeriesCode0
Positive Difference Distribution for Image Outlier Detection using Normalizing Flows and Contrastive Data—0
RUAD: unsupervised anomaly detection in HPC systems—0
Learning Informative Health Indicators Through Unsupervised Contrastive Learning—0
Self-Calibrating Anomaly and Change Detection for Autonomous Inspection Robots—0
Deep Learning-based ECG Classification on Raspberry PI using a Tensorflow Lite Model based on PTB-XL Dataset—0
Combining AI and AM - Improving Approximate Matching through Transformer NetworksCode0
ADMoE: Anomaly Detection with Mixture-of-Experts from Noisy Labels—0
Towards an Awareness of Time Series Anomaly Detection Models' Adversarial VulnerabilityCode0
LogLG: Weakly Supervised Log Anomaly Detection via Log-Event Graph Construction—0
Towards Open Set Video Anomaly Detection—0
An anomaly detection approach for backdoored neural networks: face recognition as a case studyCode0
Improving Multilayer-Perceptron(MLP)-based Network Anomaly Detection with Birch Clustering on CICIDS-2017 Dataset—0
Feature Selection for Fault Detection and Prediction based on Event Log Analysis—0
Evaluation of 3D GANs for Lung Tissue Modelling in Pulmonary CTCode0
AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection ApproachCode0
Semi-Supervised Anomaly Detection Based on Quadratic Multiform Separation—0
Data Augmentation is a Hyperparameter: Cherry-picked Self-Supervision for Unsupervised Anomaly Detection is Creating the Illusion of SuccessCode0
Locality-aware Attention Network with Discriminative Dynamics Learning for Weakly Supervised Anomaly Detection—0
Anomaly segmentation model for defects detection in electroluminescence images of heterojunction solar cells—0
Neural Embedding: Learning the Embedding of the Manifold of Physics Data—0
Machine Learning with DBOS—0
SIAD: Self-supervised Image Anomaly Detection System—0
Clear Memory-Augmented Auto-Encoder for Surface Defect Detection—0
HaloAE: An HaloNet based Local Transformer Auto-Encoder for Anomaly Detection and Localization—0
Convolutional Ensembling based Few-Shot Defect Detection Technique—0
Variational Autoencoders for Anomaly Detection in Respiratory Sounds—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