高光谱图像分类的自适应群黎曼流形学习

Q4 Engineering

International Journal of Wireless and Mobile Computing Pub Date : 2022-01-01 DOI:10.1504/ijwmc.2022.10049465

Gaodi Xu, Youlong Chen, W. Feng, R. Tang, Yao Hou, Jingru Li, Xiaofeng Xie, Haoxiang Tao

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Adaptive group Riemannian manifold learning for hyperspectral image classification

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来源期刊

International Journal of Wireless and Mobile Computing Computer Science-Computer Science (all)

CiteScore

0.80

自引率

0.00%

发文量

期刊介绍： The explosive growth of wide-area cellular systems and local area wireless networks which promise to make integrated networks a reality, and the development of "wearable" computers and the emergence of "pervasive" computing paradigm, are just the beginning of "The Wireless and Mobile Revolution". The realisation of wireless connectivity is bringing fundamental changes to telecommunications and computing and profoundly affects the way we compute, communicate, and interact. It provides fully distributed and ubiquitous mobile computing and communications, thus bringing an end to the tyranny of geography.