FACE RECOGNITION USING ENSEMBLE OF NEURAL NETWORKS

M. Alekseichevs, A. Glazs

2009

Abstract

Authors describe a novel approach for human faces recognition using ensembles (or committee) of artificial neural networks. In the task of human faces recognition there are several problems that should be considered: 1) overlapping of different sets (classes), for example, when distinguishing faces of twins; 2) the training time of neural networks can be limited. In this case it is not possible to reach correct recognition of training set during neural networks training. Therefore, the two-level hierarchical structure is used to recognize objects of examination (testing) set. As a result of neural networks training at the lower level a decisions set is formed. On the basis of the decisions set the final committee solution is constructed at the upper level. A special algorithm of weighted voting is proposed to form the committee decision. The experimental results show that the proposed algorithm is more effective in comparison with other known committee methods, when number of training iterations is limited.

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Paper Citation


in Harvard Style

Alekseichevs M. and Glazs A. (2009). FACE RECOGNITION USING ENSEMBLE OF NEURAL NETWORKS . In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8111-66-1, pages 144-149. DOI: 10.5220/0001535701440149

in Bibtex Style

@conference{icaart09,
author={M. Alekseichevs and A. Glazs},
title={FACE RECOGNITION USING ENSEMBLE OF NEURAL NETWORKS },
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2009},
pages={144-149},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001535701440149},
isbn={978-989-8111-66-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - FACE RECOGNITION USING ENSEMBLE OF NEURAL NETWORKS
SN - 978-989-8111-66-1
AU - Alekseichevs M.
AU - Glazs A.
PY - 2009
SP - 144
EP - 149
DO - 10.5220/0001535701440149