(untitled) (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Road sign recognition is an essential task in driving process to drive safely and to avoid accidents. Road sign recognition is not a simple task as there are many unfavorable factors such as bad weather, illumination, physical damage etc. The purpose of Road sign is to inform drivers and autonomous vehicles about current state of road and also provide them other important data for navigation. This paper aims to build Convolutional neural network (CNN) model to recognize road signs and to inform the drivers in advance for safe driving. The advantage of using Convolutional neural network (CNN) is its potential to build an internal representation of two-dimensional images. This enables the model to learn scale and position variant structures in the data, which is required when working with images. The proposed system achieves an accuracy of 87%.