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

Showing 44014450 of 4856 papers

TitleStatusHype
A Maritime Industry Experience for Vessel Operational Anomaly Detection: Utilizing Deep Learning Augmented with Lightweight Interpretable Models0
EndoBoost: a plug-and-play module for false positive suppression during computer-aided polyp detection in real-world colonoscopy (with dataset)0
End-to-End Abnormality Detection in Medical Imaging0
End-To-End Anomaly Detection for Identifying Malicious Cyber Behavior through NLP-Based Log Embeddings0
End-to-End Augmentation Hyperparameter Tuning for Self-Supervised Anomaly Detection0
End-to-End Convolutional Activation Anomaly Analysis for Anomaly Detection0
Energy-Based Anomaly Detection and Localization0
Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach0
Energy-based Models for Video Anomaly Detection0
Energy-Efficient Classification for Anomaly Detection: The Wireless Channel as a Helper0
Energy-Efficient Respiratory Anomaly Detection in Premature Newborn Infants0
Enforcing Cybersecurity Constraints for LLM-driven Robot Agents for Online Transactions0
EnGAN: Latent Space MCMC and Maximum Entropy Generators for Energy-based Models0
Engineering Risk-Aware, Security-by-Design Frameworks for Assurance of Large-Scale Autonomous AI Models0
Enhanced Anomaly Detection in Automotive Systems Using SAAD: Statistical Aggregated Anomaly Detection0
Enhanced Anomaly Detection in IoMT Networks using Ensemble AI Models on the CICIoMT2024 Dataset0
Enhanced Cyber-Physical Security through Deep Learning Techniques0
Enhanced Cyber-Physical Security Using Attack-resistant Cyber Nodes and Event-triggered Moving Target Defence0
Enhanced Federated Anomaly Detection Through Autoencoders Using Summary Statistics-Based Thresholding0
Enhanced network anomaly detection based on deep neural networks0
Enhanced Real-Time Threat Detection in 5G Networks: A Self-Attention RNN Autoencoder Approach for Spectral Intrusion Analysis0
Enhanced semi-supervised stamping process monitoring with physically-informed feature extraction0
Enhancing Abnormality Grounding for Vision Language Models with Knowledge Descriptions0
Enhancing Anomaly Detection in Financial Markets with an LLM-based Multi-Agent Framework0
Enhancing Anomaly Detection via Generating Diversified and Hard-to-distinguish Synthetic Anomalies0
Enhancing anomaly detection with topology-aware autoencoders0
Enhancing Claim Classification with Feature Extraction from Anomaly-Detection-Derived Routine and Peculiarity Profiles0
Enhancing Cybersecurity in IoT Networks: A Deep Learning Approach to Anomaly Detection0
Enhancing Functional Safety in Automotive AMS Circuits through Unsupervised Machine Learning0
Enhancing Multi-Class Anomaly Detection via Diffusion Refinement with Dual Conditioning0
Enhancing Network Anomaly Detection with Quantum GANs and Successive Data Injection for Multivariate Time Series0
Enhancing Pothole Detection and Characterization: Integrated Segmentation and Depth Estimation in Road Anomaly Systems0
Enhancing Predictive Maintenance in Mining Mobile Machinery through a TinyML-enabled Hierarchical Inference Network0
Enhancing Security in Federated Learning through Adaptive Consensus-Based Model Update Validation0
Enhancing Web Service Anomaly Detection via Fine-grained Multi-modal Association and Frequency Domain Analysis0
Ensemble2: Anomaly Detection via EVT-Ensemble Framework for Seasonal KPIs in Communication Network0
Ensemble and Random Collaborative Representation-Based Anomaly Detector for Hyperspectral Imagery0
Ensemble Grammar Induction For Detecting Anomalies in Time Series0
Ensemble Learning based Anomaly Detection for IoT Cybersecurity via Bayesian Hyperparameters Sensitivity Analysis0
Ensemble Methods for Sequence Classification with Hidden Markov Models0
Ensemble neuroevolution based approach for multivariate time series anomaly detection0
Entity Embedding-based Anomaly Detection for Heterogeneous Categorical Events0
Entropic one-class classifiers0
Env-Aware Anomaly Detection: Ignore Style Changes, Stay True to Content!0
EPASAD: Ellipsoid decision boundary based Process-Aware Stealthy Attack Detector0
Error Detection in Egocentric Procedural Task Videos0
ESAD: End-to-end Deep Semi-supervised Anomaly Detection0
Estimation of Dimensions Contributing to Detected Anomalies with Variational Autoencoders0
Estimation of Solar Spectral Irradiance Using Meteorological Data and Analysis of Optimal Conditions for Solar Power Generation0
ETLNet: An Efficient TCN-BiLSTM Network for Road Anomaly Detection Using Smartphone Sensors0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CPR-faster(TensorRT)FPS1,016Unverified
2CPR-fast(TensorRT)FPS362Unverified
3CPR(TensorRT)FPS130Unverified
4GLASSDetection AUROC99.9Unverified
5UniNetDetection AUROC99.9Unverified
6HETMMDetection AUROC99.8Unverified
7INP-Fomer ViT-L (model-unified multi-class)Detection AUROC99.8Unverified
8EfficientAD (early stopping)Detection AUROC99.8Unverified
9DDADDetection AUROC99.8Unverified
10PBASDetection AUROC99.8Unverified
#ModelMetricClaimedVerifiedStatus
1UniNetDetection AUROC99.8Unverified
2GLADDetection AUROC99.5Unverified
3UniNet(model-unified multi-class)Detection AUROC99.15Unverified
4INP-Former ViT-B (model-unified multi-class)Detection AUROC98.9Unverified
5DDADDetection AUROC98.9Unverified
6Dinomaly ViT-L (model-unified multi-class)Detection AUROC98.9Unverified
7DiffusionADDetection AUROC98.8Unverified
8GLASSDetection AUROC98.8Unverified
9TransFusionDetection AUROC98.7Unverified
10HETMMDetection AUROC98.1Unverified
#ModelMetricClaimedVerifiedStatus
1CSADAvg. Detection AUROC95.3Unverified
2PSADAvg. Detection AUROC94.9Unverified