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Deep Learning based Person Identification using Facial Images
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-1547-4386
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0003-3802-4721
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-1212-7637
2018 (engelsk)Inngår i: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Volume 225, 2018, s. 111-115Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Person identification is an important task for many applications for example in security. A person can be identified using finger print, vocal sound, facial image or even by DNA test. However, Person identification using facial images is one of the most popular technique which is non-contact and easy to implement and a research hotspot in the field of pattern recognition and machine vision. n this paper, a deep learning based Person identification system is proposed using facial images which shows higher accuracy than another traditional machine learning, i.e. Support Vector Machine.

sted, utgiver, år, opplag, sider
2018. s. 111-115
Emneord [en]
Face recognition, Person Identification, Deep Learning.
HSV kategori
Identifikatorer
URN: urn:nbn:se:mdh:diva-37091DOI: 10.1007/978-3-319-76213-5_17ISI: 000476922000017Scopus ID: 2-s2.0-85042545019ISBN: 9783319762128 (tryckt)OAI: oai:DiVA.org:mdh-37091DiVA, id: diva2:1152928
Konferanse
4th EAI International Conference on IoT Technologies for HealthCare HealthyIOT'17, 24 Oct 2017, Angers, France
Prosjekter
SafeDriver: A Real Time Driver's State Monitoring and Prediction SystemTilgjengelig fra: 2017-10-26 Laget: 2017-10-26 Sist oppdatert: 2019-08-08bibliografisk kontrollert

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Rahman, HamidurAhmed, Mobyen UddinBegum, Shahina

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