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DARecNet-BS: Unsupervised Dual-Attention Reconstruction Network for Hyperspectral Band Selection
IEEE Geoscience and Remote Sensing Letters, 2021Due to the existence of noise and spectral redundancies in hyperspectral images (HSIs), the band selection (BS) is highly required and can be achieved through the attention mechanism. However, existing BS methods fail to consider global interaction between the spectral information and spatial information in a nonlinear fashion.
Swalpa Kumar Roy +3 more
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2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2022
Shiqing Wang, Kun Qian 0015, Peng Chen
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Shiqing Wang, Kun Qian 0015, Peng Chen
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Hyperspectral band selection via region-aware latent features fusion based clustering
Information Fusion, 2022Jun Wang, Chang Tang, Zhenglai Li
exaly
MR-Selection: A Meta-Reinforcement Learning Approach for Zero-Shot Hyperspectral Band Selection
IEEE Transactions on Geoscience and Remote Sensing, 2023Jie Feng +2 more
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IGARSS 2025 - 2025 IEEE International Geoscience and Remote Sensing Symposium
Kangfei Shen +4 more
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Kangfei Shen +4 more
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Hyperspectral Band Selection via Optimal Neighborhood Reconstruction
IEEE Transactions on Geoscience and Remote Sensing, 2020Qi ï¼·ang, Fahong Zhang, Xuelong Li
exaly
Multi-Objective Unsupervised Band Selection Method for Hyperspectral Images Classification
IEEE Transactions on Image Processing, 2023Xianfeng Ou, Meng Wu, Bing Tu
exaly
Graph regularized spatial–spectral subspace clustering for hyperspectral band selection
Neural Networks, 2022Jun Wang, Chang Tang, Xiao Zheng
exaly

