Modeling and implementation of the process of recognition of traffic signs when determining the situation on the road using artificial neural networks

Abstract

Modeling and implementation of the process of recognition of traffic signs when determining the situation on the road using artificial neural networks

Евсина В.А., Широбокова С.Н., Жжонов В.А., Евсин В.А.

Incoming article date: 14.03.2022

In this article discusses the problems of determining traffic signs for driving a motor vehicle using an artificial neural network apparatus. The relevance of research at this point in time is described, as well as the advantages of using neural networks in determining traffic signs. The input data for determining traffic signs for convolutional neural networks are presented. The architecture of the convolutional neural classification network is formed, in particular, the sequence of layers of the image classification network is considered. A mathematical description of the modeling of the error function and the stochastic gradient descent method is given. A mathematical model of the learning process of an artificial neural network, as well as activation functions: linear functions and sigmoids is presented. An algorithm for forming an artificial neural network model is proposed. The learning process of this function is visualized on the graph. The result of the training is presented.

Keywords: artificial neural networks, classification, convolutional neural networks, deep learning, big data, mathematical modeling, informatics