Chinese Journal of Lasers, Volume. 52, Issue 1, 0110003(2025)

Deep Learning Method Suitable for Airborne Laser Bathymetry of Different Water Qualities

Yifan Huang1,2, Yan He1,2、*, Xiaolei Zhu1,2, and Guangxiu Xu3
Author Affiliations
  • 1Laboratory of Space Laser Information Transmission and Detection Technology, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China
  • 2Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
  • 3Naval Research Institute, Tianjin 300061, China
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    References(14)

    [4] Wang D D, Xu Q, Xing S et al. A coarse-to-fine signal detection method for airborne LiDAR bathymetry[J]. Acta Geodaetica et Cartographica Sinica, 47, 1148-1159(2018).

    [9] Yu Y J, Wang Y, Li H et al. Channel-wise attention mechanism relevant UNet-based diffraction limited fluorescence spot detection and localization[J]. Laser & Optoelectronics Progress, 60, 1412004(2023).

    [10] Tian H Y, Wang Y, Xiao H B. Full-automatic brain tumor segmentation based on multimodal recombination and scale cross-attention mechanism[J]. Chinese Journal of Lasers, 51, 2107110(2024).

    [14] Ye X S. Research on principle and data processing methods of airborne laser bathymetric technique[D](2010).

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    Yifan Huang, Yan He, Xiaolei Zhu, Guangxiu Xu. Deep Learning Method Suitable for Airborne Laser Bathymetry of Different Water Qualities[J]. Chinese Journal of Lasers, 2025, 52(1): 0110003

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    Paper Information

    Category: remote sensing and sensor

    Received: Jul. 18, 2024

    Accepted: Sep. 14, 2024

    Published Online: Jan. 20, 2025

    The Author Email: He Yan (heyan@siom.ac.cn)

    DOI:10.3788/CJL241064

    CSTR:32183.14.CJL241064

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