Oil palm plantation mapping from high-resolution remote sensing images using deep learning-Reference-Cited by-同舟云学术

Oil palm plantation mapping from high-resolution remote sensing images using deep learning

Published:2019-10-27 Issue:5 Volume:41 Page:2022-2046
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Dong Runmin¹²,Li Weijia¹²,Fu Haohuan¹²,Gan Lin¹²³,Yu Le¹²^ORCID,Zheng Juepeng¹²,Xia Maocai¹²

Affiliation:

1. Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China

2. Joint Center for Global Change Studies (JCGCS), Beijing, China

3. Department of Computer Science and Technology, Tsinghua University, Beijing, China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2019.1681604

Reference68 articles.

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2. Badrinarayanan, V., A. Kendall, and R. Cipolla. 2015. “Segnet: A Deep Convolutional Encoder-decoder Architecture for Image Segmentation,” arXiv:1511.00561.

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