Land cover classification of multispectral remote sensing images based on time-spectrum association features and multikernel boosting incremental learning-Reference-Cited by-同舟云学术

Land cover classification of multispectral remote sensing images based on time-spectrum association features and multikernel boosting incremental learning

Published:2019-10-24 Issue:04 Volume:13 Page:1
ISSN:1931-3195
Container-title:Journal of Applied Remote Sensing
language:
Short-container-title:J. Appl. Rem. Sens.

Author:

Bi Fukun¹,Hou Jinyuan¹,Wang Yuting²,Chen Jing¹,Wang Yanping¹

Affiliation:

1. North China University of Technology, School of Information Science and Technology, Beijing

2. Beijing Racobit Electronic Information Technology Co., Ltd., Department of Algorithm Research, Beiji

Funder

National Natural Science Foundation of China

Publisher

SPIE-Intl Soc Optical Eng

Subject

General Earth and Planetary Sciences

Reference34 articles.

1. Progress in Hyperspectral Remote Sensing Science and Technology in China Over the Past Three Decades

2. Land use classification in remote sensing images by convolutional neural networks;Castelluccio,2015

3. Unsupervised Feature Learning for Land-Use Scene Recognition

4. Mapping of land cover in northern California with simulated hyperspectral satellite imagery

5. Evaluation of the Chinese Fine Spatial Resolution Hyperspectral Satellite TianGong-1 in Urban Land-Cover Classification

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