Automated Human Recognition From Image Data

Dobiš, Lukáš

Automated Human Recognition From Image Data

but.event.date	23.04.2020	cs
but.event.title	Student EEICT 2020	cs
dc.contributor.author	Dobiš, Lukáš
dc.date.accessioned	2021-07-15T11:17:20Z
dc.date.available	2021-07-15T11:17:20Z
dc.date.issued	2020	cs
dc.description.abstract	This paper describes an approach for automated human recognition by using convolutional neural networks (CNN) to perform facial analysis of persons face from image data. The predicted biometric indicators are following: age, gender, facial landmarks and facial expression. Network architectures with pretrained weights for each task are described. Script of interconnected CNN is explained and its results support further proposed expansion plans for live video inference.	en
dc.format	text	cs
dc.format.extent	216-219	cs
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Proceedings I of the 26st Conference STUDENT EEICT 2020: General papers. s. 216-219. ISBN 978-80-214-5867-3	cs
dc.identifier.isbn	978-80-214-5867-3
dc.identifier.uri	http://hdl.handle.net/11012/200562
dc.language.iso	en	cs
dc.publisher	Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií	cs
dc.relation.ispartof	Proceedings I of the 26st Conference STUDENT EEICT 2020: General papers	en
dc.relation.uri	https://conf.feec.vutbr.cz/eeict/EEICT2020	cs
dc.rights	© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií	cs
dc.rights.access	openAccess	en
dc.subject	deep learning	en
dc.subject	computer vision	en
dc.subject	convolution neural networks	en
dc.subject	face detection	en
dc.subject	age estimation	en
dc.subject	gender classification	en
dc.subject	emotion classification	en
dc.title	Automated Human Recognition From Image Data	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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