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

Authors

  • Ngonadi I. Vivian  Department of Computer Science, Petroleum Training Institute, Effurun, Delta State, Nigeria
  • Orobor Anderson Ise  Information and Communication Technology, Federal University of Petroleum Resources, Effurun, Delta State, Nigeria

DOI:

https://doi.org/10.32628/CSEIT2063225

Keywords:

Examination Impersonation, Student Verification, Face Recognition, Deep Neural Network

Abstract

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.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2020-06-30

Issue

Volume 6, Issue 4, July-August-2020

Section

Research Articles

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How to Cite

[1]
Ngonadi I. Vivian, Orobor Anderson Ise, " Face Recognition Service Model for Student Identity Verification Using Deep Neural Network and Support Vector Machine (SVM)" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 4, pp.11-20, July-August-2020. Available at doi : https://doi.org/10.32628/CSEIT2063225