Název:
Traffic Sign Classification Using Deep Learning
Autoři:
Sicha, Marek Typ dokumentu: Příspěvky z konference
Jazyk:
cze
Nakladatel: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstrakt:
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.
Klíčová slova:
classification; neural networks; traffic signs Zdrojový dokument: Proceedings I of the 27st Conference STUDENT EEICT 2021: General papers, ISBN 978-80-214-5942-7
Instituce: Vysoké učení technické v Brně
(web)
Informace o dostupnosti dokumentu:
Plný text je dostupný v Digitální knihovně VUT. Původní záznam: http://hdl.handle.net/11012/200711