Lightweight Multilevel Feature Fusion Network for Hyperspectral Image Classification

Hyperspectral images (HSIs), acquired as a 3D data set, contain spectral and spatial information that is important for ground–object recognition. A 3D convolutional neural network (3DCNN) could therefore be more suitable than a 2D one for extracting multiscale neighborhood information in the spectra...

詳細記述

書誌詳細

主要な著者:	Miaomiao Liang, Huai Wang, Xiangchun Yu, Zhe Meng, Jianbing Yi, Licheng Jiao
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2021-12-01
シリーズ:	Remote Sensing
主題:	hyperspectral image (HSI) classification 3D convolution lightweight network target-guided fusion multilevel feature fusion
オンライン･アクセス:	https://www.mdpi.com/2072-4292/14/1/79
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