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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, 2022Xinwang Liu, Chang Tang, Zhenglai Li
exaly
IGARSS 2025 - 2025 IEEE International Geoscience and Remote Sensing Symposium
Kangfei Shen +4 more
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Kangfei Shen +4 more
openaire +1 more source
Graph regularized spatial–spectral subspace clustering for hyperspectral band selection
Neural Networks, 2022Xinwang Liu, Xiao Zheng, Chang Tang
exaly
Representative band selection for hyperspectral image classification
Journal of Visual Communication and Image Representation, 2017Xibin Zhao, Hai Wan
exaly
Representative Band Selection for Hyperspectral Image Classification
ISPRS International Journal of Geo-Information, 2018Lina Ke, Fuding Xie
exaly
Constrained band selection for hyperspectral imagery
IEEE Transactions on Geoscience and Remote Sensing, 2006Chein-I Chang
exaly

