Implementation of machine learning algorithms for gait recognition

dc.contributor.author	Kececi, A.
dc.contributor.author	Yildirak, A.
dc.contributor.author	Ozyazici, K.
dc.contributor.author	Ayluctarhan, G.
dc.contributor.author	Agbulut, O.
dc.contributor.author	Zincir, I.
dc.date.accessioned	2021-01-25T20:47:55Z
dc.date.available	2021-01-25T20:47:55Z
dc.date.issued	2020
dc.identifier	10.1016/j.jestch.2020.01.005
dc.identifier.issn	22150986
dc.identifier.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079130497&doi=10.1016%2fj.jestch.2020.01.005&partnerID=40&md5=5b73a47eec9c27b4862ca7020fb6122a
dc.identifier.uri	https://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/9609
dc.description.abstract	The basis of biometric authentication is that each person's physical and behavioural characteristics can be accurately defined. Many authentication techniques were developed over the years. Human gait recognition is one of these techniques. This article e
dc.language.iso	English
dc.publisher	Engineering Science and Technology, an International Journal
dc.title	Implementation of machine learning algorithms for gait recognition
dc.type	Article
dc.relation.firstpage	931
dc.relation.lastpage	937
dc.relation.volume	23
dc.relation.issue	4
dc.description.affiliations	Department of Computer Engineering, Yasar University, Agacli Yol, No.35-37, Bornova, Izmir 35100, Turkey

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