Road accidents are one of the major causes of human deaths. Among the different types of road accidents, motorcycle accidents are common and cause severe injuries. The helmet is the motorcyclist's main protection. Most countries require the use of helmets by motorcyclists, but many people fail to obey the law for various reasons. We present the development of a system using image processing and deep convolutional neural networks (CNNs) for finding motorcyclists who are violating helmet laws. The system comprises motorcycle detection, helmet vs. no-helmet classification, and motorcycle license plate recognition. We evaluate the system in terms of accuracy and speed. The system has been deployed at several locations in Bangkok and Phuket, Thailand since 2016. Early reports indicate that compliance with motorcycle helmet laws is increasing.


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    Titel :

    Helmet violation processing using deep learning


    Beteiligte:


    Erscheinungsdatum :

    01.01.2018


    Format / Umfang :

    160750 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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