Decoupling Semantic and Edge Representations for Building Footprint Extraction From Remote Sensing Images-Reference-Cited by-同舟云学术

Decoupling Semantic and Edge Representations for Building Footprint Extraction From Remote Sensing Images

Published:2023 Issue: Volume:61 Page:1-16
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Guo Haonan¹^ORCID,Su Xin²^ORCID,Wu Chen¹^ORCID,Du Bo³^ORCID,Zhang Liangpei¹^ORCID

Affiliation:

1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

2. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China

3. National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, School of Computer Science, and the Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan University, Wuhan, China

Funder

Chang’an University, Xi’an, China, through the National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10155230.pdf?arnumber=10155230

Reference46 articles.

1. Deep building footprint update network: A semi-supervised method for updating existing building footprint from bi-temporal remote sensing images

2. BRRNet: A Fully Convolutional Neural Network for Automatic Building Extraction From High-Resolution Remote Sensing Images

3. Fully Convolutional Networks for Multisource Building Extraction From an Open Aerial and Satellite Imagery Data Set

4. Dual attention network for scene segmentation;fu;arXiv 1809 02983,2018

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