Autonomous vehicles and machines are prepared to travel on public roads. Drivers and autonomous cars find it more challenging to recognize every traffic sign along a route as traffic density increases. Neglecting the possibility of ignoring important indications that could cause deadly mishaps is not an option. In order to regulate traffic, enforce driver behaviour. and prevent collisions. property damage, and fatalities, traffic signs are crucial. An essential component of any Intelligent Transportation System (ITS) is automated traffic sign identification and recognition. Automated traffic sign recognition and identification is crucial in the era of self- driving cars. An autonomous deep learning-based traffic sign awareness method for India is presented in this research study. This research study analyzes a novel strategyv for identifying and recognizing traffic signs that Integrates deep Iearning techniques with image processing techniques. Based on deep learning, the Convolution Neural Network (CNN) technology provides higher recognition accuracy for traffic signs, according to experimental results.


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    Titel :

    Survey on Traffic Sign Recognition Using Computer Vision Technologies


    Beteiligte:
    Nandhakumar, C. (Autor:in) / A, Rajashiva (Autor:in) / B, Srinithi (Autor:in) / K, Velmurugan (Autor:in)


    Erscheinungsdatum :

    2024-03-11


    Format / Umfang :

    421761 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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