Original title: Classification Of Traffic Signs By Convolutional Neural Networks
Authors: Mivalt, Filip ; Nejedly, Petr
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: The paper presented here describes traffic signs classification method based on a convolutional neural network (CNN). The CNN was trained and tested on the public database of German traffic signs with 43 mostly used traffic sign types. Proposed technique achieved overall classification F1 score 89.97 percent on a hidden testing dataset.
Keywords: Convolutional neural networks; Machine learning; Traffic signs recognition
Host item entry: Proceedings of the 24th Conference STUDENT EEICT 2018, ISBN 978-80-214-5614-3

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/11012/138209

Permalink: http://www.nusl.cz/ntk/nusl-393395


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