Chinese Journal of Liquid Crystals and Displays, Volume. 38, Issue 5, 680(2023)

Road object detection algorithm based on improved YOLOv5s

Qing ZHOU1,2, Gong-quan TAN1,2、*, Song-lin YIN1,2, Yi-nian LI1,2, and Dan-qin WEI1,2
Author Affiliations
  • 1School of Automation and Information Engineering,Sichuan University of Science & Engineering,Zigong 643000,China
  • 2Artificial Intelligence Key Laboratory of Sichuan Province,Yibin 644000,China
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    References(21)

    [4] GUO X J, SUI H D. Application of improved YOLOv3 in foreign object debris target detection on airfield pavement[J]. Computer Engineering and Applications, 57, 249-255(2021).

    [14] CAO Z W. Research on key technologies of pedestrian detection in vehicle image[D](2021).

    [15] GE Q, LIANG Q K, ZOU K L et al. Detection of inkjet code quality based on lightweight network and embedded system[J]. Control Engineering of China, 29, 2349-2356(2022).

    [16] HOU Z Q, HAN C Z. A survey of visual tracking[J]. Acta Automatica Sinica, 32, 603-617(2006).

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    Qing ZHOU, Gong-quan TAN, Song-lin YIN, Yi-nian LI, Dan-qin WEI. Road object detection algorithm based on improved YOLOv5s[J]. Chinese Journal of Liquid Crystals and Displays, 2023, 38(5): 680

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    Paper Information

    Category: Research Articles

    Received: Jul. 30, 2022

    Accepted: --

    Published Online: Jul. 4, 2023

    The Author Email: Gong-quan TAN (tgq77@126.com)

    DOI:10.37188/CJLCD.2022-0257

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