Laser & Optoelectronics Progress, Volume. 62, Issue 2, 0228002(2025)

Fine Classification of Tree Species Based on Improved U-Net Network

Yulin Cai1、*, Hongzhen Gao1, Xiaole Fan1, Huiyu Xu1, Zhengjun Liu2, and Geng Zhang2
Author Affiliations
  • 1College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, Shandong , China
  • 2Chinese Academy of Surveying and Mapping, Beijing 100036, China
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    [33] Xiao T C, Chen Y H, Li Y K et al. Research on crop disease recognition model based on improved channel attention mechanism[J]. Jiangsu Agricultural Sciences, 51, 168-175(2023).

    [34] Zhao P, Zhou Y X. A DA-YOLO defect detection algorithm based on attention mechanism[J]. Journal of China Jiliang University, 35, 326-332, 348(2024).

    [35] Pang C, Wang C A, Su Y et al. Rice disease detection method based on improved YOLOv8n[J]. Journal of Inner Mongolia Agricultural University (Natural Science Edition), 45, 62-68(2024).

    [36] 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).

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    Yulin Cai, Hongzhen Gao, Xiaole Fan, Huiyu Xu, Zhengjun Liu, Geng Zhang. Fine Classification of Tree Species Based on Improved U-Net Network[J]. Laser & Optoelectronics Progress, 2025, 62(2): 0228002

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Apr. 26, 2024

    Accepted: May. 24, 2024

    Published Online: Jan. 6, 2025

    The Author Email:

    DOI:10.3788/LOP241175

    CSTR:32186.14.LOP241175

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