Comparing Fully Deep Convolutional Neural Networks for Land Cover Classification with High-Spatial-Resolution Gaofen-2 Images

Comparing Fully Deep Convolutional Neural Networks for Land Cover Classification with High-Spatial-Resolution Gaofen-2 Images

Land cover is an important variable of the terrestrial ecosystem that provides information for natural resources management, urban sprawl detection, and environment research. To classify land cover with high-spatial-resolution multispectral remote sensing imagery is a difficult problem due to hetero...

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Bibliographic Details
Main Authors:	Zemin Han, Yuanyong Dian, Hao Xia, Jingjing Zhou, Yongfeng Jian, Chonghuai Yao, Xiong Wang, Yuan Li
Format:	Article
Language:	English
Published:	MDPI AG 2020-07-01
Series:	ISPRS International Journal of Geo-Information
Subjects:	deep learning classification land cover full convolutional network Unet Segnet
Online Access:	https://www.mdpi.com/2220-9964/9/8/478

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