Acta Optica Sinica, Volume. 44, Issue 24, 2401008(2024)

Classification of Missed Layers in CALIPSO Products Based on U-Net Neural Network

Yilin Geng1, Lin Zang2,3、*, Feiyue Mao1, Weiwei Xu1, and Wei Gong4
Author Affiliations
  • 1School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, Hubei , China
  • 2Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, Hubei , China
  • 3Key Laboratory of Polar Environmental Monitoring and Public Governance (Wuhan University), Ministry of Education, Wuhan 430079, Hubei , China
  • 4Electronic Information School, Wuhan University, Wuhan 430079, Hubei , China
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    References(29)

    [1] Li M Y. The atmospheric space-borne lidar cloud and aerosol classification algorithms[D](2018).

    [2] Li M Y, Fan M, Tao J H et al. The space-borne lidar cloud and aerosol classification algorithms[J]. Spectroscopy and Spectral Analysis, 39, 383-391(2019).

    [3] Yu N N. Cloud-aerosol satellite borne lidar data retrieval algorithms’ preliminary study[D](2012).

    [16] Liu D, Xu C K, Chen S J. A cloud aerosol hierarchical classification method based on semantic segmentation[P].

    [22] Wang Z E, Sassen K. Level 2 cloud scenario classification product process description and interface control document[J]. Version, 5, 50(2007).

    [24] Siddique N, Paheding S, Elkin C P et al. U-net and its variants for medical image segmentation: a review of theory and applications[J]. IEEE Access, 9, 82031-82057(2031).

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    Yilin Geng, Lin Zang, Feiyue Mao, Weiwei Xu, Wei Gong. Classification of Missed Layers in CALIPSO Products Based on U-Net Neural Network[J]. Acta Optica Sinica, 2024, 44(24): 2401008

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    Paper Information

    Category: Atmospheric Optics and Oceanic Optics

    Received: Apr. 23, 2024

    Accepted: Jun. 18, 2024

    Published Online: Dec. 16, 2024

    The Author Email: Zang Lin (zanglin2018@whu.edu.cn)

    DOI:10.3788/AOS240893

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