Traffic Sign Classification Using Deep Learning

but.event.date27.04.2021cs
but.event.titleSTUDENT EEICT 2021cs
dc.contributor.authorSicha, Marek
dc.date.accessioned2021-07-21T07:06:55Z
dc.date.available2021-07-21T07:06:55Z
dc.date.issued2021cs
dc.description.abstractThe 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.en
dc.formattextcs
dc.format.extent79-82cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings I of the 27st Conference STUDENT EEICT 2021: General papers. s. 79-82. ISBN 978-80-214-5942-7cs
dc.identifier.isbn978-80-214-5942-7
dc.identifier.urihttp://hdl.handle.net/11012/200711
dc.language.isocscs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings I of the 27st Conference STUDENT EEICT 2021: General papersen
dc.relation.urihttps://conf.feec.vutbr.cz/eeict/index/pages/view/ke_stazenics
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectclassificationen
dc.subjectneural networksen
dc.subjecttraffic signsen
dc.titleTraffic Sign Classification Using Deep Learningen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs

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