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Face Recognition Service Model for Student Identity Verification Using Deep Neural Network and Support Vector Machine (SVM)

Domain:

education

Record type:

paper
Creator:
VivIse
Publisher:
Zenodo
Host:avatar
Impersonation in the context of examination, is a situation where a candidate sits in an examination for another candidate pretending to the real candidate. In many institutions in Nigeria, to mitigate this act, students are expected to present a means of identification before entering the examination hall. However, this approach is not sufficient to determine the eligibility of a student for an examination as these means of identification can easily be falsified. This paper therefore, develops a face recognition web service model for student identity verification using Deep Neural Network (DNN) and Support Vector Machine (SVM). The aim is to mitigate examination impersonation by simple face scan using mobile phone and also to make such a model accessible and re-usable for seamless integration with any kind of student identity verification project.

Visit

doi.org

Tasks

computer vision

Tags

Examination ImpersonationStudent VerificationFace RecognitionDeep Neural Network

Licenses

Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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