With the rapid growth of people’s living standards and national economic levels, the increase of per capita vehicles leads to the exponential boost in urban traffic congestion. To solve the existing problems of traffic congestion, a deep learning architecture based on yolov4 was proposed to realize monitoring of vehicles, which is used for the real-time detection and statistics of traffic stream information. The result shows that the mean average precision (mAP) of vehicle detection can reach 85% under different occasions of light, traffic flow and vehicle speed. The method has strong environmental adaptability and broad applicability.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Real-Time Vehicle Detection Based on YOLOv4 Neutral Network


    Additional title:

    Lecture Notes on Data Engineering and Communications Technologies


    Contributors:
    Ahmad, Ishfaq (editor) / Ye, Jun (editor) / Liu, Weidong (editor) / Lai, Liping (author) / Wang, Han (author) / Lin, Dashi (author)

    Conference:

    International conference on Smart Technologies and Systems for Internet of Things ; 2021 December 19, 2021 - December 19, 2021



    Publication date :

    2022-07-03


    Size :

    6 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Accurate Real-time Ship Target detection Using Yolov4

    Wang, Bingde / Han, Bing / Yang, Liutao | IEEE | 2021


    Vehicle Detection System using YOLOv4

    Vashishtha, Srishti / Kumar, Suraj / Bothra, Vishakha et al. | IEEE | 2022


    Real‐time traffic cone detection for autonomous driving based on YOLOv4

    Qinghua Su / Haodong Wang / Min Xie et al. | DOAJ | 2022

    Free access

    Real‐time traffic cone detection for autonomous driving based on YOLOv4

    Su, Qinghua / Wang, Haodong / Xie, Min et al. | Wiley | 2022

    Free access

    Application of lightweight YOLOv4 in vehicle detection

    Tian, Feng / Wu, Lichen / Fu, Weibo et al. | British Library Conference Proceedings | 2022