Chinese Journal of Liquid Crystals and Displays, Volume. 39, Issue 1, 111(2024)

Improved YOLOv5 lightweight binocular vision UAV obstacle avoidance algorithm based on Ghost module

Yifan JIA1,2, Tianyi CAO3, and Yue BAI1、*
Author Affiliations
  • 1Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences,Changchun 130033,China
  • 2University of Chinese Academy of Sciences,Beijing 100049,China
  • 3SWJTU-Leeds Joint School,Chengdu 610097,China
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    References(19)

    [1] LI L, XU Y, JIANG Q et al. New development trends of military UAV equipment and technology in the world in 2018[J]. Tactical Missile Technology, 1-11(2019).

    [2] YAN C, TU L H, WANG Y H et al. Application of unmanned aerial vehicle in civil field in China[J]. Flight Dynamics, 40, 1-6(2022).

    [4] HUANG C P, MAO P J, LI P J et al. Research and trend of autonomous flight technology of agricultural UAV[J]. Journal of Chinese Agricultural Mechanization, 41, 162-170(2020).

    [11] YANG J J, GAO X Y, LI H L et al. Research on UAV obstacle avoidance system based on machine vision[J]. Journal of Chinese Agricultural Mechanization, 41, 155-160(2020).

    [16] BOYER R S, MOORE J S[M]. A Computational Logic Handbook: Formerly Notes and Reports in Computer Science and Applied Mathematics(2014).

    [17] MARTULL S, MARTORELL M P, FUKUI K. Realistic CG stereo image dataset with ground truth disparity maps[C], 117-118(2012).

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    Yifan JIA, Tianyi CAO, Yue BAI. Improved YOLOv5 lightweight binocular vision UAV obstacle avoidance algorithm based on Ghost module[J]. Chinese Journal of Liquid Crystals and Displays, 2024, 39(1): 111

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    Paper Information

    Category: Research Articles

    Received: Feb. 21, 2023

    Accepted: --

    Published Online: Mar. 27, 2024

    The Author Email: Yue BAI (baiy@ciomp.?ac.cn)

    DOI:10.37188/CJLCD.2023-0069

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