DGCC-EB: Deep Global Context Construction With an Enabled Boundary for Land Use Mapping of CSMA-Reference-Cited by-同舟云学术

DGCC-EB: Deep Global Context Construction With an Enabled Boundary for Land Use Mapping of CSMA

Published:2022 Issue: Volume:60 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Zhang Hanchao¹^ORCID,Zang Ning¹,Cao Yun²,Wang Yuebin¹^ORCID,Zhang Liqiang³^ORCID,Huang Bo⁴^ORCID,Mathiopoulos P. Takis⁵^ORCID

Affiliation:

1. School of Land Science and Technology, China University of Geosciences, Beijing, China

2. Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing, China

3. Beijing Key Laboratory of Environmental Remote Sensing and Digital Cities, Faculty of Geographical, Beijing Normal University, Beijing, China

4. Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong

5. Department of Informatics and Telecommunications, National and Kapodestrian University of Athens, Athens, Greece

Funder

National Natural Science Foundation of China

Special Fund of Chinese Central Government for Basic Scientific Research Operations in Commonweal Research Institutes

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09963942.pdf?arnumber=9963942

Reference66 articles.

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4. Deep learning for superpixel-based classification of remote sensing images

5. Superpixel-Based Graphical Model for Remote Sensing Image Mapping