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dc.contributor.authorRajnoha, Martin
dc.date.accessioned2020-04-16T07:19:37Z
dc.date.available2020-04-16T07:19:37Z
dc.date.issued2019cs
dc.identifier.citationProceedings of the 25st Conference STUDENT EEICT 2019. s. 500-504. ISBN 978-80-214-5735-5cs
dc.identifier.isbn978-80-214-5735-5
dc.identifier.urihttp://hdl.handle.net/11012/186723
dc.description.abstractFace recognition systems can play significant role in our every day lives. This paper proposes a scalable system for person identification based on face recognition methods and its implementation that utilizes queues, containers and microservices architecture. The proposed system uses a GPU acceleration therefore it can run in real-time. It utilizes two deep neural networks – Single Shot Multibox Detector (SSD) for a face detection and Facenet for a face recognition.en
dc.formattextcs
dc.format.extent500-504cs
dc.format.mimetypeapplication/pdfen
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.subjectfacerecognitionen
dc.subjectscalableen
dc.subjectrealtimeen
dc.subjectdetectionen
dc.subjectmicroservicesen
dc.subjectqueuesen
dc.subjectidentificationen
dc.titleScalable Person Identification System For Real-Time Applicationsen
eprints.affiliatedInstitution.departmentFakulta elektrotechniky a komunikačních technologiícs
but.event.date25.04.2019cs
but.event.titleStudent EEICT 2019cs
dc.rights.accessopenAccessen
dc.type.driverconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionPublishers's versionen


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