Use of YOLOv4 and Yolov4Tiny for Intelligent Vehicle Detection in Smart City Environments
- Daniel H. de la Iglesia
- Héctor Sánchez San Blas
- Vivian F. López
- María N. Moreno-García
- M. Dolores Muñoz Vicente
- Raul Garcia Ovejero
- Gabriel Villarrubia
- Juan F. de Paz Santana
- Daniel H. de la Iglesia (ed. lit.)
- Juan F. de Paz Santana (ed. lit.)
- Alfonso J. López Rivero (ed. lit.)
Editorial: Springer International Publishing AG
ISBN: 978-3-031-14858-3
Año de publicación: 2023
Páginas: 265-274
Congreso: DiTTEt: International Conference on Disruptive Technologies, Tech Ethics and Artificial Intelligence (2. 2022. Salamanca)
Tipo: Aportación congreso
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.