Integrating support vector machines and neural networks

Authors:
Rosario Capparuccia;Renato De Leone;Emilia Marchitto
Affiliations:
Sigma S.p.A. Via Po, 14, 63010 Altidona (AP), Italy;Dipartimento di Matematica e Informatica, Universití degli Studi di Camerino, Via Madonna delle Carceri, 9, 62032 Camerino (MC), Italy;Dipartimento di Matematica e Informatica, Universití degli Studi di Camerino, Via Madonna delle Carceri, 9, 62032 Camerino (MC), Italy
Venue:
Neural Networks
Year:
2007

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Abstract

Support vector machines (SVMs) are a powerful technique developed in the last decade to effectively tackle classification and regression problems. In this paper we describe how support vector machines and artificial neural networks can be integrated in order to classify objects correctly. This technique has been successfully applied to the problem of determining the quality of tiles. Using an optical reader system, some features are automatically extracted, then a subset of the features is determined and the tiles are classified based on this subset.