Jin-Qiang Yao

Uncertainty-Driven Cyclic Background Purification for Hyperspectral Anomaly Detection

Hyperspectral anomaly detection (HAD) aims to identify spectrally distinct and spatially sparse targets from complex backgrounds without prior anomaly labels. In recent years, reconstruction-based deep learning (DL) methods have achieved detection by modeling the background distribution. However, due to the influence o...