Deep Spectral Spatial Inverted Residual Network for Hyperspectral Image Classification

Convolutional neural networks (CNNs) have been widely used in hyperspectral image classification in recent years. The training of CNNs relies on a large amount of labeled sample data. However, the number of labeled samples of hyperspectral data is relatively small. Moreover, for hyperspectral images...

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Autors principals:	Tianyu Zhang, Cuiping Shi, Diling Liao, Liguo Wang
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2021-11-01
Col·lecció:	Remote Sensing
Matèries:	hyperspectral image classification deep feature extraction inverted residual convolution network global 3D attention
Accés en línia:	https://www.mdpi.com/2072-4292/13/21/4472
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