Nowadays, technology is growing very fast with automation in all aspects and still research is going on to introduce more and more algorithms to reduce human work. In this regard, Artificial intelligence is playing a major role. One of the greatest inventions using artificial intelligence is automated vehicles. In which there is no need for human interaction to drive the vehicle. Utmost care should be taken for the safe driving of autonomous vehicles. For autonomous cars or vehicles, recognition of the traffic signs is the major consideration for safe driving. So, to recognize and classify the traffic signs on the road, in this paper proposed method is Traffic sign recognition using CNN and Keras frameworks using a deep learning algorithm. CNN is the best algorithm used in so many image analysis tasks like image recognition and object detection. Not only may this strategy be used to minimize accidents caused by human error, but it can also be used to reduce accidents caused by human error. An accuracy of 96.8% was achieved using this method.


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    Titel :

    Traffic Sign Recognition Using CNN


    Beteiligte:


    Erscheinungsdatum :

    23.04.2022


    Format / Umfang :

    955179 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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