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Deep Learning based Person Identification using Facial Images
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1547-4386
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-3802-4721
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1212-7637
2017 (English)In: 4th EAI International Conference on IoT Technologies for HealthCare HealthyIOT'17, 2017Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
2017.
Keyword [en]
Face recognition, Person Identification, Deep Learning.
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-37091OAI: oai:DiVA.org:mdh-37091DiVA: diva2:1152928
Conference
4th EAI International Conference on IoT Technologies for HealthCare HealthyIOT'17, 24 Oct 2017, Angers, France
Projects
SafeDriver: A Real Time Driver's State Monitoring and Prediction System
Available from: 2017-10-26 Created: 2017-10-26 Last updated: 2017-10-26Bibliographically approved

Open Access in DiVA

No full text

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Rahman, HamidurAhmed, Mobyen UddinBegum, Shahina

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Citation style
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