Dirty road extraction from GF-2 images by semi-supervised deep learning method for arid and semiarid regions of southern Mongolia-Reference-Cited by-同舟云学术

Dirty road extraction from GF-2 images by semi-supervised deep learning method for arid and semiarid regions of southern Mongolia

Published:2024-07-30 Issue:1 Volume:17 Page:
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Wang Meng¹²,Wang Juanle¹²³

Affiliation:

1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research of Chinese Academy of Sciences, Beijing, People’s Republic of China

2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, People’s Republic of China

3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, People’s Republic of China

Funder

National Key Research and Development Program

Key R&D and Achievement Transformation Plan Project of the Inner Mongolia Autonomous Region

Key Project of Innovation LREIS

Construction Project of the China Knowledge Center for Engineering Sciences and Technology

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2024.2384631

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