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

Authors

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%.

Downloads

Download data is not yet available.

Downloads

Published

10-01-2018

How to Cite

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

Funding data