Open AccessAdvanced Driver Assistance System using Convolutional Neural Network
Author(s) -
et. al. Geetha
Publication year - 2021
Publication title -
türk bilgisayar ve matematik eğitimi dergisi
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 3
ISSN - 1309-4653
DOI - 10.17762/turcomat.v12i2.1098
Subject(s) - convolutional neural network , computer science , task (project management) , process (computing) , traffic sign recognition , sign (mathematics) , artificial intelligence , advanced driver assistance systems , representation (politics) , computer vision , artificial neural network , traffic sign , engineering , mathematical analysis , mathematics , systems engineering , politics , law , political science , operating system
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%.