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 47514775 of 4856 papers

TitleStatusHype
Variational Inference for On-line Anomaly Detection in High-Dimensional Time Series0
Finding Needle in a Million Metrics: Anomaly Detection in a Large-scale Computational Advertising Platform0
Semi-Markov Switching Vector Autoregressive Model-based Anomaly Detection in Aviation Systems0
Anomaly Detection in Clutter using Spectrally Enhanced Ladar0
A landmark-based algorithm for automatic pattern recognition and abnormality detection0
GraphPrints: Towards a Graph Analytic Method for Network Anomaly Detection0
Expected Similarity Estimation for Large-Scale Batch and Streaming Anomaly DetectionCode0
Learning Minimum Volume Sets and Anomaly Detectors from KNN Graphs0
A Survey on Social Media Anomaly Detection0
Variational Autoencoder based Anomaly Detection using Reconstruction ProbabilityCode0
An unsupervised spatiotemporal graphical modeling approach to anomaly detection in distributed CPS0
ATD: Anomalous Topic Discovery in High Dimensional Discrete DataCode0
Continuous online sequence learning with an unsupervised neural network modelCode0
Energy-Efficient Classification for Anomaly Detection: The Wireless Channel as a Helper0
Unsupervised Trajectory Clustering via Adaptive Multi-Kernel-Based Shrinkage0
Extracting Information from Indian First Names0
Real-Time Anomaly Detection and Localization in Crowded Scenes0
Real-Time Anomalous Behavior Detection and Localization in Crowded Scenes0
Canonical Autocorrelation Analysis0
EdgeCentric: Anomaly Detection in Edge-Attributed Networks0
Constant Time EXPected Similarity Estimation using Stochastic Optimization0
ALOJA: A Framework for Benchmarking and Predictive Analytics in Big Data Deployments0
ALOJA-ML: A Framework for Automating Characterization and Knowledge Discovery in Hadoop Deployments0
Learning Deep Representations of Appearance and Motion for Anomalous Event Detection0
Anomaly Detection in Unstructured Environments using Bayesian Nonparametric Scene Modeling0
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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