The automatic recognition technology of traffic signs is crucial in the process of autonomous driving. This paper aims to solve the low recognition rate of traffic signs due to complex background interference. This study realizes the improvement of detection accuracy of the trained YOLOv3 model by adjusting the relevant parameters in the YOLOv3 model, retraining the data set, and finding the appropriate threshold value, and finally realizing the accurate recognition of traffic signs.


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    Titel :

    Real-Time Traffic Sign Detection Based on Improved YOLO V3


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Liu, Qi (Herausgeber:in) / Liu, Xiaodong (Herausgeber:in) / Chen, Bo (Herausgeber:in) / Zhang, Yiming (Herausgeber:in) / Peng, Jiansheng (Herausgeber:in) / Zeng, Haini (Autor:in)


    Erscheinungsdatum :

    12.11.2021


    Format / Umfang :

    6 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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