Nowadays, two-wheeler vehicles are often considered less safe for traveling due to a rising number of accidents attributed to the disregard of traffic rules. To address this issue, governments have implemented various plans aimed at ensuring better adherence to these rules. One significant measure has been the increase in penalty amounts, which has played a role in maintaining better control over road safety.However, this has also presented challenges for traffic authorities in effectively monitoring the substantial volume of traffic. The introduction of Automatic License Plate Recognition (ALPR) allowed the real-time monitoring of rule breakage. This enabled parking management, toll collections, tracking stolen cars, detecting law breakage, etc. This paper provides proper understanding of different methodologies used for recognition of license plates. In addition, we implemented a vehicle plate recognitionframework using ConvolutionNeural Network that compared to previous research work excelled in overall performance.


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    Titel :

    Automatic Two Wheeler License Plate Recognition Using Deep Learning Techniques


    Beteiligte:


    Erscheinungsdatum :

    01.11.2023


    Format / Umfang :

    1294746 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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