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 23012325 of 4856 papers

TitleStatusHype
An Iterative Method for Unsupervised Robust Anomaly Detection Under Data Contamination0
Detection of Shilling Attack Based on T-distribution on the Dynamic Time Intervals in Recommendation Systems0
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications0
Identifying Backdoor Attacks in Federated Learning via Anomaly Detection0
Detection of Object Throwing Behavior in Surveillance Videos0
Detection of Global Anomalies on Distributed IoT Edges with Device-to-Device Communication0
Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models0
An Introduction to Autoencoders0
Integrating Graph Neural Networks with Scattering Transform for Anomaly Detection0
Acoustic Anomaly Detection for Machine Sounds based on Image Transfer Learning0
ABCD: Trust enhanced Attention based Convolutional Autoencoder for Risk Assessment0
Detection of fraudulent financial papers by picking a collection of characteristics using optimization algorithms and classification techniques based on squirrels0
Detection of Fights in Videos: A Comparison Study of Anomaly Detection and Action Recognition0
Detection of Emerging Infectious Diseases in Lung CT based on Spatial Anomaly Patterns0
Detection of Dataset Shifts in Learning-Enabled Cyber-Physical Systems using Variational Autoencoder for Regression0
An Input-to-State Safety Approach Towards Safe Control of a Class of Parabolic PDEs Under Disturbances0
Detection of Anomalies in Multivariate Time Series Using Ensemble Techniques0
Detection of anomalies in cow activity using wavelet transform based features0
Detection of Anomalies and Faults in Industrial IoT Systems by Data Mining: Study of CHRIST Osmotron Water Purification System0
Advancing Cyber-Attack Detection in Power Systems: A Comparative Study of Machine Learning and Graph Neural Network Approaches0
Detection of Abnormal Vessel Behaviours from AIS data using GeoTrackNet: from the Laboratory to the Ocean0
Detection of Abnormal Behavior with Self-Supervised Gaze Estimation0
Are vision language models robust to uncertain inputs?0
Détection d’anomalies textuelles à base de l’ingénierie d’invite (Prompt Engineering-Based Text Anomaly Detection )0
D\'etection automatique d'anomalies sur deux styles de parole dysarthrique: parole lue vs spontan\'ee (Automatic anomaly detection for dysarthria across two speech styles : read vs spontaneous speech)0
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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