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 3351–3400 of 4856 papers

TitleStatusHype
A Massively Parallel Associative Memory Based on Sparse Neural Networks—0
An Investigation of Traffic Density Changes inside Wuhan during the COVID-19 Epidemic with GF-2 Time-Series Images—0
A Method for Detecting Abnormal Data of Network Nodes Based on Convolutional Neural Network—0
A method for incremental discovery of financial event types based on anomaly detection—0
A Methodological Report on Anomaly Detection on Dynamic Knowledge Graphs—0
A Methodology for the Diagnostic of Aircraft Engine Based on Indicators Aggregation—0
Am I Rare? An Intelligent Summarization Approach for Identifying Hidden Anomalies—0
‘Am I the Bad One’? Predicting the Moral Judgement of the Crowd Using Pre–trained Language Models—0
A Model-Free Kullback-Leibler Divergence Filter for Anomaly Detection in Noisy Data Series—0
A Modified Dynamic Time Warping (MDTW) Approach and Innovative Average Non-Self Match Distance (ANSD) Method for Anomaly Detection in ECG Recordings—0
A Modular and Unified Framework for Detecting and Localizing Video Anomalies—0
Grading and Anomaly Detection for Automated Retinal Image Analysis using Deep Learning—0
A multi-domain splitting framework for time-varying graph structure—0
A Multi-Level Approach for Class Imbalance Problem in Federated Learning for Remote Industry 4.0 Applications—0
A Multi-modal one-class generative adversarial network for anomaly detection in manufacturing—0
A multi-model approach using XAI and anomaly detection to predict asteroid hazards—0
A Multi-perspective Approach To Anomaly Detection For Self-aware Embodied Agents—0
A Multi-Scale A Contrario method for Unsupervised Image Anomaly Detection—0
A Multi-Step Comparative Framework for Anomaly Detection in IoT Data Streams—0
A multi-stream deep neural network with late fuzzy fusion for real-world anomaly detection—0
A Multi-View Framework for BGP Anomaly Detection via Graph Attention Network—0
An Adaptive Approach for Anomaly Detector Selection and Fine-Tuning in Time Series—0
An Adaptive Event-based Data Converter for Always-on Biomedical Applications at the Edge—0
An ADMM-based Optimal Transmission Frequency Management System for IoT Edge Intelligence—0
An AI-Based Public Health Data Monitoring System—0
Analysis of Vision-based Abnormal Red Blood Cell Classification—0
Analytical Discovery of Manifold with Machine Learning—0
Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks—0
Analytical Probability Distributions and EM-Learning for Deep Generative Networks—0
Analytics and Machine Learning Powered Wireless Network Optimization and Planning—0
Analyzing Business Process Anomalies Using Autoencoders—0
ACE -- An Anomaly Contribution Explainer for Cyber-Security Applications—0
An Anomaly Detection Method for Satellites Using Monte Carlo Dropout—0
An Anomaly Detection System Based on Generative Classifiers for Controller Area Network—0
An Asymmetric Loss with Anomaly Detection LSTM Framework for Power Consumption Prediction—0
An Attention-based ConvLSTM Autoencoder with Dynamic Thresholding for Unsupervised Anomaly Detection in Multivariate Time Series—0
An Attention-Based Deep Generative Model for Anomaly Detection in Industrial Control Systems—0
An Attention Free Conditional Autoencoder For Anomaly Detection in Cryptocurrencies—0
An Attribute Oriented Induction based Methodology for Data Driven Predictive Maintenance—0
An Automated Analysis Framework for Trajectory Datasets—0
An Automated Data Engineering Pipeline for Anomaly Detection of IoT Sensor Data—0
An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction—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
An Autonomous Drone Swarm for Detecting and Tracking Anomalies among Dense Vegetation—0
An Efficient Anomaly Detection Approach using Cube Sampling with Streaming Data—0
An Efficient Approach for Anomaly Detection in Traffic Videos—0
Building an Efficient Intrusion Detection System Based on Feature Selection and Ensemble Classifier—0
An Efficient One-Class SVM for Anomaly Detection in the Internet of Things—0
An Efficient Outlier Detection Algorithm for Data Streaming—0
An Empirical Review of Deep Learning Frameworks for Change Detection: Model Design, Experimental Frameworks, Challenges and Research Needs—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