FUZZY TEMPLATES FOR PAIR-WISE MULTI-CLASS CLASSIFICATION

Rimantas Kybartas

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Paper

FUZZY TEMPLATES FOR PAIR-WISE MULTI-CLASS CLASSIFICATION

Topics: Classification; Multi-Agent Learning; Object Recognition

In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, 564-567, 2012 , Vilamoura, Algarve, Portugal

Author: Rimantas Kybartas

Affiliation: Vilnius University, Lithuania

Keyword(s): Fuzzy Templates, Single layer perceptron, Support Vectors, Pair-wise classifiers, Multi-class classification.

Related Ontology Subjects/Areas/Topics: Applications ; Classification ; Multi-Agent Learning ; Object Recognition ; Pattern Recognition ; Software Engineering ; Theory and Methods

Abstract: In this paper, a pair-wise classifier fusion by Fuzzy Templates is analyzed. Single layer perceptron and support vectors are used as pair-wise classifiers. Comments on weakness and strength of such fusion method are presented. The obtained results show, that in some cases such an approach could be competitive or even outperform other pair-wise classifier fusion methods.

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Paper citation in several formats:

Kybartas, R. (2012). FUZZY TEMPLATES FOR PAIR-WISE MULTI-CLASS CLASSIFICATION. In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-8425-99-7; ISSN 2184-4313, SciTePress, pages 564-567. DOI: 10.5220/0003766505640567

@conference{icpram12,
author={Rimantas Kybartas.},
title={FUZZY TEMPLATES FOR PAIR-WISE MULTI-CLASS CLASSIFICATION},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2012},
pages={564-567},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003766505640567},
isbn={978-989-8425-99-7},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - FUZZY TEMPLATES FOR PAIR-WISE MULTI-CLASS CLASSIFICATION
SN - 978-989-8425-99-7
IS - 2184-4313
AU - Kybartas, R.
PY - 2012
SP - 564
EP - 567
DO - 10.5220/0003766505640567
PB - SciTePress