Author

Fang-Qiang Kong

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2026

D3A-Net: A Deformable 3-D Attention Network for Hyperspectral Unmixing

Hyperspectral unmixing (HU) aims to decompose mixed pixels into endmember spectra and corresponding abundance maps under physically interpretable constraints. Despite recent progress in convolutional neural network (CNN)- and Transformer-based approaches, most existing methods still rely on rigid sampling grids or proc...

Fang-Qiang Kong, Hao-Cheng Yang, Zhi-Bo Wu et al. · IEEE Transactions on Geoscie... · 0 citations

2026

Learned Hyperspectral Image Compression With Coarse-to-Fine Spatial–Spectral Prediction Network

While deep-learned hyperspectral image (HSI) compression has achieved remarkable progress, existing methods typically encode latent representations indiscriminately. This entangled paradigm fails to separate global structural priors from local spectral details, thereby bottlenecking the overall spectral fidelity. To ad...

Fang-Qiang Kong, Qian Li, Peng-Ji Xie et al. · IEEE Transactions on Geoscie... · 0 citations