ObjFormer: Learning Land-Cover Changes From Paired OSM Data and Optical High-Resolution Imagery via Object-Guided Transformer-Reference-Cited by-同舟云学术

ObjFormer: Learning Land-Cover Changes From Paired OSM Data and Optical High-Resolution Imagery via Object-Guided Transformer

Published:2024 Issue: Volume:62 Page:1-22
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Chen Hongruixuan¹^ORCID,Lan Cuiling²^ORCID,Song Jian³^ORCID,Broni-Bediako Clifford⁴^ORCID,Xia Junshi⁴^ORCID,Yokoya Naoto³^ORCID

Affiliation:

1. Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba, Japan

2. Microsoft Research Asia, Beijing, China

3. Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Chiba, Japan

4. RIKEN Center for Advanced Intelligence Project, Tokyo, Japan

Funder

Council for Science, Technology and Innovation

Cross-Ministerial Strategic Innovation Promotion Program

National Research Institute for Earth Science and Disaster Resilience (NIED) through the Development of a Resilient Smart Network System against Natural Disasters

Japan Society for the Promotion of Science (JSPS) KAKENHI

Japan Science and Technology Agency (JST) FOREST

Microsoft Research Asia

Next Generation AI Research Center, The University of Tokyo

Graduate School of Frontier Sciences, The University of Tokyo, through the Challenging New Area Doctoral Research Grant

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/36/10354519/10551264.pdf?arnumber=10551264

Reference74 articles.

1. Review Article Digital change detection techniques using remotely-sensed data

2. Review ArticleDigital change detection methods in ecosystem monitoring: a review

3. Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods

4. Building damage assessment for rapid disaster response with a deep object-based semantic change detection framework: From natural disasters to man-made disasters

5. On China’s earth observation system: mission, vision and application

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