Defect Detection In Fibered Material Using Methods Of Machine Learning

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but.event.date25.04.2019cs
but.event.titleStudent EEICT 2019cs
dc.contributor.authorLang, Matěj
dc.date.accessioned2020-04-16T07:19:33Z
dc.date.available2020-04-16T07:19:33Z
dc.date.issued2019cs
dc.description.abstractSILON s.r.o is manufacturer of polyester fibres which get used in wide range of applications, many of them requiring highest quality material. Due to manufacturing processes, some fibres are not drawn properly and stay in the fiber as bundles, or brittle, thick threads. Proposed lab station should automate process of quality check of each batch. It consists of linescan camera scanner and computer with software for detection and analysis of defects.en
dc.formattextcs
dc.format.extent331-334cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationProceedings of the 25st Conference STUDENT EEICT 2019. s. 331-334. ISBN 978-80-214-5735-5cs
dc.identifier.isbn978-80-214-5735-5
dc.identifier.urihttp://hdl.handle.net/11012/186685
dc.language.isoencs
dc.publisherVysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.relation.ispartofProceedings of the 25st Conference STUDENT EEICT 2019en
dc.relation.urihttp://www.feec.vutbr.cz/EEICT/cs
dc.rights© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologiícs
dc.rights.accessopenAccessen
dc.subjectEEICTen
dc.subjectpolyester fiberen
dc.subjectfluorescenceen
dc.subjectRhodamine Ben
dc.subjectscanneren
dc.subjectlinescan cameraen
dc.subjectquality checken
dc.subjectdefect detectionen
dc.subjectCNNen
dc.subjectconvolutional neural networken
dc.subjectFCNen
dc.subjectfully convolutional networken
dc.titleDefect Detection In Fibered Material Using Methods Of Machine Learningen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
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