Structure-Aware Weakly Supervised Network for Building Extraction From Remote Sensing Images-Reference-Cited by-同舟云学术

Structure-Aware Weakly Supervised Network for Building Extraction From Remote Sensing Images

Published:2022 Issue: Volume:60 Page:1-12
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Chen Hui¹^ORCID,Cheng Liang¹^ORCID,Zhuang Qizhi¹,Zhang Ka²^ORCID,Li Ning¹,Liu Lei¹^ORCID,Duan Zhixin¹^ORCID

Affiliation:

1. Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, China

2. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09931751.pdf?arnumber=9931751

Reference52 articles.

1. WTS: A Weakly towards Strongly Supervised Learning Framework for Remote Sensing Land Cover Classification Using Segmentation Models