Turkish Journal of Computer and Mathematics Education
Journal license

Journal

Turkish Journal of Computer and Mathematics Education


Volume
& Issue

Volume 12, Issue 3


Published
on

April 5, 2021


Pages

4244-4250


DOI

Article

Traffic Sign Classification Using Convolutional Neural Networks and Computer Vision


Authors

Anuraag Velamati Affiliation:
School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India
and Gopichand G* Affiliation:
School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India


Abstract

The world is quickly and continuously advancing towards better technological advancements that will make life quite easier for us, human beings [22]. Humans are looking for more interactive and advanced ways to improve their learning. One such dream is making a machine think like a computer, which lead to innovations like AI and deep learning [25]. The world is running at a higher pace in the domain of AI, deep learning, robotics and machine learning Using this knowledge and technology, we could develop anything right now [36]. As a part of sub-domain, the introduction of Convolution Neural Networks made deep learning extensively strong in the domain of image classification and detection [1]. The research that we have conducted is one of its kind. Our research used Convolution Neural Network, TensorFlow and Keras.


Keywords

Convolutional Neural Networks, TensorFlow, Deep learning, Traffic signs


Citation

Velamati, A. & G, G. (2021). Traffic sign classification using convolutional neural networks and computer vision. Turkish Journal of Computer and Mathematics Education, 12(3), 4244–4250.

Published by: Engineering Journals

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