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2026

Frequency-Aware Bias Calibration Attention Network for Hyperspectral Image Classification

Recently, self-attention mechanisms have significantly advanced hyperspectral image classification (HSIC) by enabling effective modeling of long-range spatial–spectral dependencies. However, existing methods often suffer from blurred land-cover boundaries and insufficient discriminability between spectrally similar cla...

Zhen-Qiu Shu, Nan-Bo Liu, Ke-Xin Zeng et al. · 0 citations
2026

Sparse Tensor Attention for Hyperspectral Unmixing

Hyperspectral unmixing (HU) is a fundamental task for resolving the mixed pixel problem by decomposing a hyperspectral image (HSI) into constituent endmembers and their corresponding abundances. Although deep-learning-based HU methods have achieved promising performance, most rely on manually designed network architect...

Jing-Ran Wang, Feng-Chao Xiong, Zhiyuan Wen et al. · 0 citations

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