One of the biggest problems in cities today is the significant increase in the number of motor vehicles. Intelligent traffic control is a fundamental part of controlling city travel. To achieve this goal, it is very important to have sensor technologies capable of identifying the number of vehicles traveling on a road. In this paper, we propose the development of a classifier model capable of reliably counting the number of vehicles in urban areas. In this case, it is proposed the construction of a dataset to carry out the training of a model based on YOLOv4 and YOLOv4Tiny systems that can be embedded in intelligent traffic light systems.


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    Title :

    Use of YOLOv4 and Yolov4Tiny for Intelligent Vehicle Detection in Smart City Environments


    Additional title:

    Advs in Intelligent Syst., Computing



    Conference:

    International Conference on Disruptive Technologies, Tech Ethics and Artificial Intelligence ; 2022 ; Salamanca, Spain July 20, 2022 - July 22, 2022



    Publication date :

    2022-08-28


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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