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DARecNet-BS: Unsupervised Dual-Attention Reconstruction Network for Hyperspectral Band Selection

IEEE Geoscience and Remote Sensing Letters, 2021
Due 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
openaire   +1 more source

BS-SiamRPN: Hyperspectral Video Tracking based on Band Selection and the Siamese Region Proposal Network

2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2022
Shiqing Wang, Kun Qian 0015, Peng Chen
openaire   +1 more source

Hyperspectral band selection via region-aware latent features fusion based clustering

Information Fusion, 2022
Xinwang Liu, Chang Tang, Zhenglai Li
exaly  

BS-ConvKAN: Hyperspectral Band Selection Based on Sparsified KAN Convolution and Hybrid Teacher Guidance

IGARSS 2025 - 2025 IEEE International Geoscience and Remote Sensing Symposium
Kangfei Shen   +4 more
openaire   +1 more source

Representative band selection for hyperspectral image classification

Journal of Visual Communication and Image Representation, 2017
Xibin Zhao, Hai Wan
exaly  

Representative Band Selection for Hyperspectral Image Classification

ISPRS International Journal of Geo-Information, 2018
Lina Ke, Fuding Xie
exaly  

Constrained band selection for hyperspectral imagery

IEEE Transactions on Geoscience and Remote Sensing, 2006
Chein-I Chang
exaly  

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