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Supervised Anomaly Detection

In the training set, the amount of abnormal samples is limited and significant fewer than normal samples, producing data distributions that lead to a naturally imbalanced learning problem.

Papers

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Showing 1–25 of 155 papers

TitleStatusHype
Self-supervised Anomaly Detection Pretraining Enhances Long-tail ECG DiagnosisCode2
Few-Shot Anomaly-Driven Generation for Anomaly Classification and SegmentationCode2
Spatial-aware Attention Generative Adversarial Network for Semi-supervised Anomaly Detection in Medical ImageCode1
SAD: Semi-Supervised Anomaly Detection on Dynamic GraphsCode1
Semi-supervised Anomaly Detection using AutoEncodersCode1
SLA^2P: Self-supervised Anomaly Detection with Adversarial PerturbationCode1
Learning to Adapt to Unseen Abnormal Activities under Weak SupervisionCode1
Catching Both Gray and Black Swans: Open-set Supervised Anomaly DetectionCode1
On Diffusion Modeling for Anomaly DetectionCode1
RoSAS: Deep Semi-Supervised Anomaly Detection with Contamination-Resilient Continuous SupervisionCode1
Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly DetectionCode1
Natural Synthetic Anomalies for Self-Supervised Anomaly Detection and LocalizationCode1
Change-point detection in wind turbine SCADA data for robust condition monitoring with normal behaviour modelsCode1
Feature Encoding with AutoEncoders for Weakly-supervised Anomaly DetectionCode1
NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly GenerationCode1
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly DetectionCode1
Consistency-based Self-supervised Learning for Temporal Anomaly LocalizationCode1
ImbSAM: A Closer Look at Sharpness-Aware Minimization in Class-Imbalanced RecognitionCode1
Contrastive Transformer-based Multiple Instance Learning for Weakly Supervised Polyp Frame DetectionCode1
DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly DetectionCode1
Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly DataCode1
ProDisc-VAD: An Efficient System for Weakly-Supervised Anomaly Detection in Video Surveillance ApplicationsCode1
Explainable Deep Few-shot Anomaly Detection with Deviation NetworksCode1
Diffusion Models for Medical Anomaly DetectionCode1
Supervised Anomaly Detection for Complex Industrial ImagesCode1
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