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

• Autores: Daniel Hernández de la Iglesia , Hector Sánchez San Blas, Vivian Félix López Batista , María Navelonga Moreno García , María Dolores Muñoz Vicente, Raul García Ovejero, Gabriel Villarrubia González , Juan Francisco de Paz Santana
• Localización: New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence: The DITTET 2022 Collection / Daniel Hernández de la Iglesia (ed. lit.) , Juan Francisco de Paz Santana (ed. lit.) , Alfonso José López Rivero (ed. lit.) , 2023, ISBN 978-3-031-14858-3, págs. 265-274
• Idioma: español
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• Resumen

  • 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.