Comparison of Different Neural Network Training Algorithms with Application to Face Recognition

Authors

  • A. Vulovic University of Kragujevac
  • T. Sustersic University of Kragujevac
  • A. Peulic University of Kragujevac
  • N. Filipovic University of Kragujevac
  • V. Rankovic University of Kragujevac

DOI:

https://doi.org/10.4108/eai.10-1-2018.153550

Keywords:

face recognition, neural network, Eigenface algorithm

Abstract

Research in the field of face recognition has been popular for several decades. With advances in technology, approaches to solving this problems haves changed. Main goal of this paper was to compare different training algorithms for neural networks and to apply them for face recognition as it is a nonlinear problem. Algorithm that we have used for face recognition problem was the Eigenface algorithm that belongs to the Principal Component Analysis (PCA) algorithms. Percentage of recognition for all the used training functions is above 90%.

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Published

10-01-2018

Issue

Vol. 4 No. 12 (2018): EAI Endorsed Transactions on Industrial Networks and Intelligent Systems

Section

Research articles

License

This is an open-access article distributed under the terms of the Creative Commons Attribution CC BY 3.0 license, which permits unlimited use, distribution, and reproduction in any medium so long as the original work is properly cited.

How to Cite

Comparison of Different Neural Network Training Algorithms with Application to Face Recognition. (2018). EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 4(12), e3. https://doi.org/10.4108/eai.10-1-2018.153550