GACP: graph neural networks with ARMA filters and a parallel CNN for hyperspectral image classification

GACP: graph neural networks with ARMA filters and a parallel CNN for hyperspectral image classification

In recent years, the use of convolutional neural networks (CNNs) and graph neural networks (GNNs) to identify hyperspectral images (HSIs) has achieved excellent results, and such methods are widely used in agricultural remote sensing, geological exploration, and marine remote sensing. Although many...

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Bibliographic Details
Main Authors: Jing Yang, Jie Sun, Yaping Ren, Shaobo Li, Shujie Ding, Jianjun Hu
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:International Journal of Digital Earth
Subjects:
graph neural networks word
convolutional neural networks
hyperspectral image classification
attention mechanisms
Online Access:http://dx.doi.org/10.1080/17538947.2023.2210310

Internet

http://dx.doi.org/10.1080/17538947.2023.2210310

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