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Publication detail
SICHA, M.
Original Title
Traffic Sign classification using Deep Learning
English Title
Type
article in a collection out of WoS and Scopus
Language
Czech
Original 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 the Python programming language were chosen to solve the problem. To solve the problem a machine learning method was chosen, more precisely a convolutional neural network. A neural network in the Python programming language was created for the classification of traffic signs, using the Keras and Tensorflow libraries. The neural network architecture is chosen for optimization for use on a single-board computer with limited performance.
English abstract
Keywords
classification, neural networks, traffic signs
Key words in English
Authors
Released
27. 4. 2021
Publisher
Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Location
Brno
ISBN
978-80-214-5942-7
Book
Proceedings I of the 27th Conference STUDENT EEICT 2021
Edition number
1
Pages from
Pages to
4
Pages count
BibTex
@inproceedings{BUT171556, author="Marek {Sicha}", title="Traffic Sign classification using Deep Learning", booktitle="Proceedings I of the 27th Conference STUDENT EEICT 2021", year="2021", number="1", pages="1--4", publisher="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií", address="Brno", isbn="978-80-214-5942-7" }