Class-Guided Swin Transformer for Semantic Segmentation of Remote Sensing Imagery-Reference-Cited by-同舟云学术

Class-Guided Swin Transformer for Semantic Segmentation of Remote Sensing Imagery

Published:2022 Issue: Volume:19 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Meng Xiaoliang¹,Yang Yuechi¹,Wang Libo¹^ORCID,Wang Teng²,Li Rui³^ORCID,Zhang Ce⁴^ORCID

Affiliation:

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

2. Lands and Resource Department of Guangdong Province, Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China, Ministry of Natural Resources, Surveying and Mapping Institute, Guangzhou, China

3. Intelligent Control and Smart Energy (ICSE) Research Group, School of Engineering, University of Warwick, Coventry, U.K.

4. Lancaster Environment Centre, Lancaster University, Lancaster, U.K.

Funder

Key Laboratory of Natural Resources Monitoring in Tropical and Subtropical Area of South China, Ministry of Natural Resources

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/9651998/09921210.pdf?arnumber=9921210

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