Laser & Optoelectronics Progress, Volume. 59, Issue 18, 1828003(2022)

Object Detection of Individual Mangrove Based on Improved YOLOv5

Yongkang Ma1,2, Hua Liu1,2、*, Chengxing Ling1,2, Feng Zhao1,2, Yi Jiang1,2, and Yutong Zhang1,2
Author Affiliations
  • 1Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China
  • 2Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Beijing 100091, China
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    Figures & Tables(12)
    Partial drone images of individual mangrove
    YOLOv5 network structure
    Schematic of Focus structure and slice
    Structure diagram of ECA mechanism
    SoftPool structure diagram
    Position of SoftPool in YOLOv5-ECA
    Overview diagram of the label box. (a) Label of object; (b) normalized target location map; (c) normalized target size map
    Curve of the loss function value varying with epoch
    mAP value of YOLOv4
    Comparison of parameter convergence results
    Recall-Precision curves. (a) YOLOv5; (b) YOLOv5-ECA
    Result of object detection. (a) Detection result of YOLOv5; (b) detection result of YOLOv5-ECA
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    Yongkang Ma, Hua Liu, Chengxing Ling, Feng Zhao, Yi Jiang, Yutong Zhang. Object Detection of Individual Mangrove Based on Improved YOLOv5[J]. Laser & Optoelectronics Progress, 2022, 59(18): 1828003

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Jul. 18, 2021

    Accepted: Aug. 10, 2021

    Published Online: Aug. 29, 2022

    The Author Email: Hua Liu (liuhua@ifrit.ac.cn)

    DOI:10.3788/LOP202259.1828003

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