Change Detection From Synthetic Aperture Radar Images via Graph-Based Knowledge Supplement Network-Reference-Cited by-同舟云学术

Change Detection From Synthetic Aperture Radar Images via Graph-Based Knowledge Supplement Network

Published:2022 Issue: Volume:15 Page:1823-1836
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Wang Junjie¹^ORCID,Gao Feng¹^ORCID,Dong Junyu¹^ORCID,Zhang Shan²,Du Qian³^ORCID

Affiliation:

1. School of Computer Science and Technology, Ocean University of China, Qingdao, China

2. Meteorological Bureau of Tianjin Municipality, Tianjin, China

3. Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS, USA

Funder

National Key Research and Development Program of China

Key Technology Research and Development Program of Shandong

Natural Science Foundation of Shandong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

Reference51 articles.

Cited by 38 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

2. A TomoSAR regularization-based method for height change detection in urban areas;International Journal of Applied Earth Observation and Geoinformation;2024-05