Laser & Optoelectronics Progress, Volume. 62, Issue 4, 0428006(2025)

Remote Sensing Scene Classification Method Based on Multi-Scale Graph Convolution Context Feature Aggregation

Baolan Chen1,2,3、*, Huawang Li1,2,3, and Yinxiao Wang1,2,3
Author Affiliations
  • 1Innovation Academy for Microsatellites, Chinese Academy of Sciences, Shanghai 201204, China
  • 2School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
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    References(32)

    [10] Yu T W, Zheng E R, Shen J G et al. Optical remote sensing image scene classification based on multi-level cross-layer bilinear fusion[J]. Acta Photonica Sinica, 51, 0210007(2022).

    [12] He Q, Zhang J Y, Huang D M et al. RA-ProtoNet: classification based on meta-learning for few-shot remote sensing scene[J]. Laser & Optoelectronics Progress, 60, 1028003(2023).

    [17] He X J, Liu X, Wei X. Classification method of high-resolution remote sensing scene image based on dictionary learning and vision transformer[J]. Laser & Optoelectronics Progress, 60, 1410019(2023).

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    Baolan Chen, Huawang Li, Yinxiao Wang. Remote Sensing Scene Classification Method Based on Multi-Scale Graph Convolution Context Feature Aggregation[J]. Laser & Optoelectronics Progress, 2025, 62(4): 0428006

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Jun. 12, 2024

    Accepted: Jul. 25, 2024

    Published Online: Feb. 18, 2025

    The Author Email:

    DOI:10.3788/LOP241466

    CSTR:32186.14.LOP241466

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