A Triple-Path Spectral–Spatial Network With Interleave-Attention for Hyperspectral Image Classification

To exploit hyperspectral image's (HSI) spectral–spatial information and reduce network complexity, a triple-path convolution neural network with an interleave-attention mechanism is constructed for high-precision classification. A hybrid branch is proposed to capture joint features, wh...

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Détails bibliographiques

Auteurs principaux:	Ziqing Deng, Yang Wang, Bing Zhang, Linwei Li, Jihong Wang, Lifeng Bian, Chen Yang
Format:	Artigo
Langue:	Inglês
Publié:	IEEE 2022-01-01
Collection:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Sujets:	Hyperspectral image (HSI) classification interleave-attention spectral and spatial attention block spectral–spatial feature extraction triple-path network (TP-Net)
Accès en ligne:	https://ieeexplore.ieee.org/document/9833261/
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