Laser & Optoelectronics Progress, Volume. 61, Issue 18, 1828001(2024)

Change Detection of Optical and Synthetic Aperture Radar Remote Sensing Images Based on a Domain Adaptive Neural Network

Qinfeng Yao1、*, Yongxiang Ning1, and Sunwen Du2
Author Affiliations
  • 1Department of Earth Science and Engineering, Shanxi Institute of Engineering and Technology, Yangquan 045000, Shanxi, China
  • 2School of Mining Engineering, Taiyuan University of Technology, Taiyuan 030024, Shanxi, China
  • show less
    References(23)

    [5] Gong X, Chen Z L, Wu L et al. Transfer learning based mixture of experts classification model for high-resolution remote sensing scene classification[J]. Acta Optica Sinica, 41, 2301003(2021).

    [10] Fan J, Jia F W, Wu C D. Remote sensing images change detection based on secondary clustering[J]. Laser Journal, 44, 49-53(2023).

    [15] Ni L B, Lu H Y, Lu T J et al. Remote sensing image change detection based on twin residual neural network[J]. Computer Engineering and Design, 41, 3451-3457(2020).

    [16] Wang C H, Li E Z, Xiao M. Multi-feature fusion and twin attention networks for high resolution Remote sensing image object detection[J]. Journal of Jilin University (Engineering and Technology Edition), 54, 240-250(2024).

    Tools

    Get Citation

    Copy Citation Text

    Qinfeng Yao, Yongxiang Ning, Sunwen Du. Change Detection of Optical and Synthetic Aperture Radar Remote Sensing Images Based on a Domain Adaptive Neural Network[J]. Laser & Optoelectronics Progress, 2024, 61(18): 1828001

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Remote Sensing and Sensors

    Received: Nov. 27, 2023

    Accepted: Jan. 26, 2024

    Published Online: Sep. 14, 2024

    The Author Email: Qinfeng Yao (yx20231123@163.com)

    DOI:10.3788/LOP232565

    CSTR:32186.14.LOP232565

    Topics