Formation of neural network layers for solving the problem of classification of road signs
Abstract
Formation of neural network layers for solving the problem of classification of road signs
Incoming article date: 26.11.2022This article discusses the formation and connection of layers in the task of classifying images of traffic signs, as well as calculating weights on the corresponding layers of the neural network. The authors describe the biological structure of brain neurons, as well as their comparison with artificial neural networks. A conceptual model of an artificial neuron and a neural network with a description of structural elements is presented. The matrix structure of the weights of the neural network is given. The process of converting an RGB image of a road sign into an input layer of a neural network is described. A corresponding description is provided for each hidden layer. In addition, a description of the convolution layers and the maximum pool is given, as well as an explanation of the need to use this type of layers in a convolutional neural network. The authors also described an algorithm for the formation of a convolutional neural network for the classification of road signs. Examples of the operation of this neural network are given.
Keywords: convolutional neural networks, classification, deep learning, big data, mathematical modeling, computer science