A New RBF Classifier for Buried Tag Recognition

Larbi Beheim, Adel Zitouni, Fabien Belloir

Abstract

This article presents noticeable performances improvement of an RBF neural classifier. Based on the Mahalanobis distance, this new classifier increases relatively the recognition rate while decreasing remarkably the number of hidden layer neurons. We obtain thus a new very general RBF classifier, very simple, not requiring any adjustment parameter, and presenting an excellent ratio performances/neurons number. A comparative study of its performances is presented and illustrated by examples on real databases. We present also the recognition improvements obtained by applying this new classifier on buried tag.

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Paper Citation


in Harvard Style

Beheim L., Zitouni A. and Belloir F. (2005). A New RBF Classifier for Buried Tag Recognition . In Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2005) ISBN 972-8865-28-7, pages 22-32. DOI: 10.5220/0002562800220032


in Bibtex Style

@conference{pris05,
author={Larbi Beheim and Adel Zitouni and Fabien Belloir},
title={A New RBF Classifier for Buried Tag Recognition},
booktitle={Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2005)},
year={2005},
pages={22-32},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002562800220032},
isbn={972-8865-28-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems - Volume 1: PRIS, (ICEIS 2005)
TI - A New RBF Classifier for Buried Tag Recognition
SN - 972-8865-28-7
AU - Beheim L.
AU - Zitouni A.
AU - Belloir F.
PY - 2005
SP - 22
EP - 32
DO - 10.5220/0002562800220032