In recent years, research towards Autonomous Vehicle (AV) has grown up tremendously. The introduction of Advanced Driving Assistance System (ADAS) in AV has led researchers to explore on the key functionalities that an AV should have, proposes to create a convenience and safe environment where there is no input acquire from a human throughout the journey. One of the key functionalities is the Traffic Sign Recognition (TSR). Hence, this study aims to develop a real-time traffic sign recognition system that can recognize Malaysian traffic sign in real-time and to test the accuracy of the system. The Deep Learning technology using You Only Look Once (YOLO) algorithm is used to train the model for recognition. Five types of warning traffic sign including crossroad, crossroad right, crossroad left, school children crossing and bump from Malaysian traffic sign is used. The test results reached for real-time object detection is 96.00% accuracy on both traffic sign detection and recognition. The finding from this study is believed to be helpful as it may contribute to the ADAS development in the automotive industry for the self-driving vehicle.


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    Titel :

    A Real-Time Malaysian Traffic Sign Recognition Using YOLO Algorithm


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Isa, Khalid (Herausgeber:in) / Md. Zain, Zainah (Herausgeber:in) / Mohd-Mokhtar, Rosmiwati (Herausgeber:in) / Mat Noh, Maziyah (Herausgeber:in) / Ismail, Zool H. (Herausgeber:in) / Yusof, Ahmad Anas (Herausgeber:in) / Mohamad Ayob, Ahmad Faisal (Herausgeber:in) / Azhar Ali, Syed Saad (Herausgeber:in) / Abdul Kadir, Herdawatie (Herausgeber:in) / Mangshor, Nur Nabilah Abu (Autor:in)


    Erscheinungsdatum :

    25.09.2021


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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