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dc.contributor.authorMíček, Vojtěch
dc.date.accessioned2021-07-15T11:17:21Z
dc.date.available2021-07-15T11:17:21Z
dc.date.issued2020cs
dc.identifier.citationProceedings I of the 26st Conference STUDENT EEICT 2020: General papers. s. 245-248. ISBN 978-80-214-5867-3cs
dc.identifier.isbn978-80-214-5867-3
dc.identifier.urihttp://hdl.handle.net/11012/200570
dc.description.abstractThe aim of this thesis is to enable evaluation of quality, or the type of product in industrial applications using artificial neural networks, especially in applications where the classical approach of machine vision is too complicated. The system thus designed is implemented onto a specific hardware platform and becomes a subject to the final optimalisation for the hardware platform for the best performance of the system.en
dc.formattextcs
dc.format.extent245-248cs
dc.format.mimetypeapplication/pdfen
dc.language.isocscs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings I of the 26st Conference STUDENT EEICT 2020: General papersen
dc.relation.urihttps://conf.feec.vutbr.cz/eeict/EEICT2020cs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.subjectNeural networksen
dc.subjectmachine visionen
dc.subjectproduct inspectionen
dc.subjectobject classificationen
dc.subjectNvidia Jetson Xavieren
dc.subjectRaspberry Pien
dc.subjectIntel Movidiusen
dc.subjectOpenCVen
dc.subjectKerasen
dc.subjectTensorFlowen
dc.titleNeural Networks For Visual Classification And Inspection Of The Industrial Productsen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
but.event.date23.04.2020cs
but.event.titleStudent EEICT 2020cs
dc.rights.accessopenAccessen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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