Abstract
AbstractOne 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.KeywordsTrafficDetectionDeep learningComputer VisionDatasetintelligent traffic light system
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