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 2051–2100 of 4856 papers

TitleStatusHype
Anomaly Detection with Inexact Labels—0
A Multi-View Framework for BGP Anomaly Detection via Graph Attention Network—0
Creating an Atlas of Normal Tissue for Pruning WSI Patching Through Anomaly Detection—0
CRD: Collaborative Representation Distance for Practical Anomaly Detection—0
Anomaly Detection with HMM Gauge Likelihood Analysis—0
CRC-SGAD: Conformal Risk Control for Supervised Graph Anomaly Detection—0
CRCL: Causal Representation Consistency Learning for Anomaly Detection in Surveillance Videos—0
Anomaly Detection with Generative Adversarial Networks—0
Feature Extraction for Novelty Detection in Network Traffic—0
GCAD: Anomaly Detection in Multivariate Time Series from the Perspective of Granger Causality—0
CRATOS: Cognition of Reliable Algorithm for Time-series Optimal Solution—0
A multi-stream deep neural network with late fuzzy fusion for real-world anomaly detection—0
CRADL: Contrastive Representations for Unsupervised Anomaly Detection and Localization—0
ANOMALY DETECTION WITH FRAME-GROUP ATTENTION IN SURVEILLANCE VIDEOS—0
A Deep-Learning Method Using Auto-encoder and Generative Adversarial Network for Anomaly Detection on Ancient Stone Stele Surfaces—0
GAN-based Anomaly Detection in Imbalance Problems—0
A Multi-Step Comparative Framework for Anomaly Detection in IoT Data Streams—0
Anomaly Detection with Ensemble of Encoder and Decoder—0
GAL-MAD: Towards Explainable Anomaly Detection in Microservice Applications Using Graph Attention Networks—0
COVID-19 Detection Using CT Image Based On YOLOv5 Network—0
Anomaly Detection with Domain Adaptation—0
GAN Augmented Text Anomaly Detection with Sequences of Deep Statistics—0
Efficient GAN-based method for cyber-intrusion detection—0
Coupled IGMM-GANs for deep multimodal anomaly detection in human mobility data—0
Coupled Attention Networks for Multivariate Time Series Anomaly Detection—0
Counterfactual Explanation for Auto-Encoder Based Time-Series Anomaly Detection—0
A Deep Learning Generative Model Approach for Image Synthesis of Plant Leaves—0
Anomaly Detection with Convolutional Autoencoders for Fingerprint Presentation Attack Detection—0
A Comparative Study of Machine Learning Algorithms for Anomaly Detection in Industrial Environments: Performance and Environmental Impact—0
A Multi-Scale A Contrario method for Unsupervised Image Anomaly Detection—0
GADY: Unsupervised Anomaly Detection on Dynamic Graphs—0
GAN-based Multiple Adjacent Brain MRI Slice Reconstruction for Unsupervised Alzheimer's Disease Diagnosis—0
Correlated discrete data generation using adversarial training—0
Anomaly Detection With Conditional Variational Autoencoders—0
Correlated Attention in Transformers for Multivariate Time Series—0
Correlated Anomaly Detection from Large Streaming Data—0
Anomaly detection with a variational autoencoder for Arabic mispronunciation detection—0
A Multi-perspective Approach To Anomaly Detection For Self-aware Embodied Agents—0
Corn Yield Prediction based on Remotely Sensed Variables Using Variational Autoencoder and Multiple Instance Regression—0
Anomaly Detection with Adversarially Learned Perturbations of Latent Space—0
Coresets for Data Discretization and Sine Wave Fitting—0
Copula Quadrant Similarity for Anomaly Scores—0
A multi-model approach using XAI and anomaly detection to predict asteroid hazards—0
A Deep Learning Framework for Generation and Analysis of Driving Scenario Trajectories—0
Copula-based anomaly scoring and localization for large-scale, high-dimensional continuous data—0
cOOpD: Reformulating COPD classification on chest CT scans as anomaly detection using contrastive representations—0
A Multi-modal one-class generative adversarial network for anomaly detection in manufacturing—0
Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection—0
A Comparative Analysis of Machine Learning Techniques for IoT Intrusion Detection—0
Convolutional Recurrent Reconstructive Network for Spatiotemporal Anomaly Detection in Solder Paste Inspection—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