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 4451–4500 of 4856 papers

TitleStatusHype
Active Anomaly Detection with Switching Cost—0
Spectral Embedding Norm: Looking Deep into the Spectrum of the Graph LaplacianCode0
Machine Learning for Anomaly Detection and Categorization in Multi-cloud Environments—0
Fast Adaptive RNN Encoder-Decoder for Anomaly Detection in SMD Assembly MachineCode0
Unsupervised Detection of Anomalous Sound based on Deep Learning and the Neyman-Pearson LemmaCode0
QANet: Tensor Decomposition Approach for Query-based Anomaly Detection in Heterogeneous Information Networks—0
A Stacked Autoencoder Neural Network based Automated Feature Extraction Method for Anomaly detection in On-line Condition Monitoring—0
Unsupervised Anomalous Data Space Specification—0
A Roadmap Towards Resilient Internet of Things for Cyber-Physical Systems—0
MDGAN: Boosting Anomaly Detection Using \ -Discriminator Generative Adversarial Networks—0
Real time expert system for anomaly detection of aerators based on computer vision technology and existing surveillance cameras—0
Spatially-weighted Anomaly Detection—0
CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densitiesCode0
Distributed optimization in wireless sensor networks: an island-model framework—0
Clustering-based Anomaly Detection for microservices—0
GLAD: GLocalized Anomaly Detection via Human-in-the-Loop LearningCode1
Landmine Detection Using Autoencoders on Multi-polarization GPR Volumetric DataCode0
WAIC, but Why? Generative Ensembles for Robust Anomaly DetectionCode0
Measuring sentence parallelism using Mahalanobis distances: The NRC unsupervised submissions to the WMT18 Parallel Corpus Filtering shared task—0
The Profiling Machine: Active Generalization over Knowledge—0
Interactive Surveillance Technologies for Dense Crowds—0
Active Anomaly Detection via EnsemblesCode1
Multiple Abnormality Detection for Automatic Medical Image Diagnosis Using Bifurcated Convolutional Neural Network—0
A Virtual Testbed for Critical Incident Investigation with Autonomous Remote Aerial Vehicle Surveying, Artificial Intelligence, and Decision Support—0
Identification of temporal transition of functional states using recurrent neural networks from functional MRI—0
Online Cyber-Attack Detection in Smart Grid: A Reinforcement Learning ApproachCode0
Real-Time Nonparametric Anomaly Detection in High-Dimensional SettingsCode0
Anomaly Detection with Generative Adversarial Networks for Multivariate Time SeriesCode0
Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction—0
Convolutional Graph Auto-encoder: A Deep Generative Neural Architecture for Probabilistic Spatio-temporal Solar Irradiance Forecasting—0
Does Your Phone Know Your Touch?—0
Coupled IGMM-GANs for deep multimodal anomaly detection in human mobility data—0
Multi-level hypothesis testing for populations of heterogeneous networks—0
Anomaly Detection in the Presence of Missing Values—0
An Open Access Database for Evaluating the Algorithms of Electrocardiogram Rhythm and Morphology Abnormality Detection—0
DeepFall -- Non-invasive Fall Detection with Deep Spatio-Temporal Convolutional AutoencodersCode0
AAD: Adaptive Anomaly Detection through traffic surveillance videos—0
Surface Defect Saliency of Magnetic TileCode0
DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN—0
Enhanced network anomaly detection based on deep neural networks—0
Neuromorphic Architecture for the Hierarchical Temporal Memory—0
Metric Learning for Novelty and Anomaly DetectionCode0
Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral imagesCode0
Image Anomalies: a Review and Synthesis of Detection Methods—0
Robust Spectral Filtering and Anomaly Detection—0
Anomaly Detection via Minimum Likelihood Generative Adversarial Networks—0
Scalable Multi-Task Gaussian Process Tensor Regression for Normative Modeling of Structured Variation in Neuroimaging Data—0
Call Detail Records Driven Anomaly Detection and Traffic Prediction in Mobile Cellular Networks—0
Detector monitoring with artificial neural networks at the CMS experiment at the CERN Large Hadron ColliderCode0
Anomaly detection in static networks using egonets—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