Original title: Traffic Sign Classification Using Deep Learning
Authors: Sicha, Marek
Document type: Papers
Language: cze
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: The thesis focuses on the classification of traffic signs in images and video sequences.The goal is real-time processing and usage of software in the vehicle. Neural networks and thePython programming language were chosen to solve the problem. To solve the problem a machinelearning method was chosen, more precisely a convolutional neural network. A neural network inthe Python programming language was created for the classification of traffic signs, using the Kerasand Tensorflow libraries. The neural network architecture is chosen for optimization for use on asingle-board computer with limited performance.
Keywords: classification; neural networks; traffic signs
Host item entry: Proceedings I of the 27st Conference STUDENT EEICT 2021: General papers, ISBN 978-80-214-5942-7

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/200711

Permalink: http://www.nusl.cz/ntk/nusl-447756


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Universities and colleges > Public universities > Brno University of Technology
Conference materials > Papers