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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 26–50 of 155 papers

TitleStatusHype
Weakly-supervised anomaly detection for multimodal data distributions—0
Pancreatic Tumor Segmentation as Anomaly Detection in CT Images Using Denoising Diffusion Models—0
Anomaly Detection by Context Contrasting—0
Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled DataCode0
Qsco: A Quantum Scoring Module for Open-set Supervised Anomaly Detection—0
Spatial-aware Attention Generative Adversarial Network for Semi-supervised Anomaly Detection in Medical ImageCode1
Semi-supervised Anomaly Detection via Adaptive Reinforcement Learning-Enabled Method with Causal Inference for Sensor SignalsCode0
MAPL: Memory Augmentation and Pseudo-Labeling for Semi-Supervised Anomaly DetectionCode0
Supervised Anomaly Detection for Complex Industrial ImagesCode1
IgCONDA-PET: Weakly-Supervised PET Anomaly Detection using Implicitly-Guided Attention-Conditional Counterfactual Diffusion Modeling -- a Multi-Center, Multi-Cancer, and Multi-Tracer StudyCode0
Machine learning-based identification of Gaia astrometric exoplanet orbitsCode0
Anomaly Detection in Electrocardiograms: Advancing Clinical Diagnosis Through Self-Supervised Learning—0
Improving Interpretability of Scores in Anomaly Detection Based on Gaussian-Bernoulli Restricted Boltzmann Machine—0
MKF-ADS: Multi-Knowledge Fusion Based Self-supervised Anomaly Detection System for Control Area Network—0
LogELECTRA: Self-supervised Anomaly Detection for Unstructured Logs—0
Weakly Supervised Anomaly Detection via Knowledge-Data Alignment—0
Semi-supervised learning via DQN for log anomaly detection—0
Hyperbolic Anomaly Detection—0
Semi-Supervised Health Index Monitoring with Feature Generation and Fusion—0
Revisiting Non-separable Binary Classification and its Applications in Anomaly DetectionCode0
NNG-Mix: Improving Semi-supervised Anomaly Detection with Pseudo-anomaly GenerationCode1
Weakly Supervised Anomaly Detection for Chest X-Ray ImageCode0
CL-Flow:Strengthening the Normalizing Flows by Contrastive Learning for Better Anomaly Detection—0
Open-Set Graph Anomaly Detection via Normal Structure Regularisation—0
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly DetectionCode1
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