JOURNAL ARTICLE

TRAFFIC SIGN CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK

Nemanja VeličkovićZeljko StojkovićGoran DimićDragan MiletićJelena VasiljevićDhinaharan Nagamalai

Year: 2018 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

<p>Artificial Neural Networks enables solving many problems in which classical computing is not up to task. Neural Networks and Deep Learning currently provide the best solutions to problems in image recognition, speech recognition and natural language processing. In this paper a Neural Network, more specific - Convolutional Neural Network solution for the purpose of recognizing and classifying road traffic signs is proposed. Such solution could be used in autonomous vehicle production, and also similar solutions could easily be implemented in any other application that requires image object recognition. </p>

Keywords:
Convolutional neural network Artificial neural network Time delay neural network Image (mathematics) Deep learning Pattern recognition (psychology) Object (grammar) Traffic sign recognition Contextual image classification

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Topics

Advanced Neural Network Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Vehicle License Plate Recognition
Physical Sciences →  Engineering →  Media Technology
Traffic Prediction and Management Techniques
Physical Sciences →  Engineering →  Building and Construction
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