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

Daniel Hernández de la Iglesia Árbol académico, Hector Sánchez San Blas, Vivian Félix López Batista Árbol académico, María Navelonga Moreno García Árbol académico, María Dolores Muñoz Vicente, Raul García Ovejero, Gabriel Villarrubia González Árbol académico, Juan Francisco de Paz Santana Árbol académico

  • 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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