Author

Fangfang Wu

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2026

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...

Ji-Cai Li, Yu-Xin Feng, Jin-Qiang Yao et al. · IEEE Transactions on Geoscie... · 0 citations

Jul 2026

ARetinex-Net: Low-light image enhancement with adaptive retinex model and global illumination representation.

An Adaptive Retinex Model (ARM) is proposed that decomposes an input image into structural (reflectance) and illumination components without relying on handcrafted priors or regularization terms and consistently outperforms state-of-the-art LLIE methods in terms of quantitative metrics and visual quality.

Yunlong Liu, Weisheng Dong, Yufan Zhu et al. · Neural Networks · 0 citations