Classification Of Traffic Signs By Convolutional
Neural Networks

Mivalt, Filip; Nejedly, Petr

Classification Of Traffic Signs By Convolutional Neural Networks

but.event.date	26.04.2018	cs
but.event.title	Student EEICT 2018	cs
dc.contributor.author	Mivalt, Filip
dc.contributor.author	Nejedly, Petr
dc.date.accessioned	2019-03-04T10:05:41Z
dc.date.available	2019-03-04T10:05:41Z
dc.date.issued	2018	cs
dc.description.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.	en
dc.format	text	cs
dc.format.extent	188-190	cs
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Proceedings of the 24th Conference STUDENT EEICT 2018. s. 188-190. ISBN 978-80-214-5614-3	cs
dc.identifier.isbn	978-80-214-5614-3
dc.identifier.uri	http://hdl.handle.net/11012/138209
dc.language.iso	en	cs
dc.publisher	Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií	cs
dc.relation.ispartof	Proceedings of the 24th Conference STUDENT EEICT 2018	en
dc.relation.uri	http://www.feec.vutbr.cz/EEICT/	cs
dc.rights	© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií	cs
dc.rights.access	openAccess	en
dc.subject	Machine learning	en
dc.subject	Convolutional neural networks	en
dc.subject	Traffic signs recognition	en
dc.title	Classification Of Traffic Signs By Convolutional Neural Networks	en
dc.type.driver	conferenceObject	en
dc.type.status	Peer-reviewed	en
dc.type.version	publishedVersion	en
eprints.affiliatedInstitution.department	Fakulta elektrotechniky a komunikačních technologií	cs

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