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    • Language-guided cross-spatiotemporal domain adaptation for remote sensing image semantic segmentation

    • The latest research breaks through the adaptive problem in the field of remote sensing images and proposes a language text guided global pre training local fine-tuning framework, significantly improving cross temporal and spatial domain transfer performance.
    • Vol. 30, Issue 9, Pages: 3153-3170(2025)   

      Received:07 November 2024

      Revised:2025-01-15

      Accepted:13 February 2025

      Published:16 September 2025

    • DOI: 10.11834/jig.240640     

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  • Tao Chao, Guo Xin, Hu Keyan, Shen Yuxiang, Wang Hao. 2025. Language-guided cross-spatiotemporal domain adaptation for remote sensing image semantic segmentation. Journal of Image and Graphics, 30(9):3153-3170 DOI: 10.11834/jig.240640.
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相关作者

Tao Chao 中南大学地球科学与信息物理学院
Guo Xin 中南大学地球科学与信息物理学院
Hu Keyan 中南大学地球科学与信息物理学院
Shen Yuxiang 中南大学地球科学与信息物理学院
Wang Hao 中南大学地球科学与信息物理学院
Jianhua Yao 宁夏回族自治区遥感测绘勘查院
Jiamin Wu 宁夏回族自治区遥感测绘勘查院
Yong Yang 宁夏回族自治区遥感测绘勘查院

相关机构

Central South University, School of Geosciences and Info-physics
Ningxia Insitute of Remote Sensing, Survey and Mapping
School of Computer and Communication Engineering, University of Science and Technology Beijing
Beijing Key Laboratory of Knowledge Engineering for Materials Science
College of Automation, Beijing Information Science and Technology University
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