Road accidents are a leading cause of fatalities, often resulting from the misinterpretation of traffic signs. Misinterpretation can occur due to driver negligence or reduced visibility caused by adverseweather conditions such as fog or heavy rain. To address this issue and prevent road accidents, we propose an innovative system that employs R-CNN for real-time traffic sign recognition. Our system operates by capturing a live feed from the vehicle's perspective and processing it in real-time. Using R- CNN, it identifies traffic sign boards and promptly notifies the driver via voice alerts. This system proves particularly valuable when visibility of traffic signs is significantly compromised due to adverse weather conditions. By recognizing and relaying crucial information, it empowers drivers to make informed decisions, thereby reducing the risk of accidents and enhancing road safety.


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    Titel :

    Traffic Sign Board Recognition and Alert System Using R-CNN




    Erscheinungsdatum :

    12.12.2023


    Format / Umfang :

    469634 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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