4 citations · 9 across the 4 of their papers we have counts for
4 papers · 1 filter
Anomaly Detection in Electrocardiograms: Advancing Clinical Diagnosis Through Self-Supervised Learning
Aofan Jiang, Chaoqin Huang, Qing Cao +5
The electrocardiogram (ECG) is an essential tool for diagnosing heart disease, with computer-aided systems improving diagnostic accuracy and reducing healthcare costs. Despite adva…
Adapting Visual-Language Models for Generalizable Anomaly Detection in Medical Images
Chaoqin Huang, Aofan Jiang, Jinghao Feng +3
Recent advancements in large-scale visual-language pre-trained models have led to significant progress in zero-/few-shot anomaly detection within natural image domains. However, th…
Multi-scale Cross-restoration Framework for Electrocardiogram Anomaly Detection
Aofan Jiang, Chaoqin Huang, Qing Cao +5
Electrocardiogram (ECG) is a widely used diagnostic tool for detecting heart conditions. Rare cardiac diseases may be underdiagnosed using traditional ECG analysis, considering tha…
Registration based Few-Shot Anomaly Detection
Chaoqin Huang, Haoyan Guan, Aofan Jiang +3
This paper considers few-shot anomaly detection (FSAD), a practical yet under-studied setting for anomaly detection (AD), where only a limited number of normal images are provided…