title: Integrating support vector machines and neural networks.
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.
authors.affiliation: Sigma S.p.A. Via Po, 14, 63010 Altidona (AP), Italy.
authors.forename: Rosario
authors.initials: R
authors.lastname: Capparuccia
authors.forename: Renato
authors.initials: R
authors.lastname: De Leone
authors.forename: Emilia
authors.initials: E
authors.lastname: Marchitto
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D016571:Neural Networks, Computer; D009716:Numerical Analysis, Computer-Assisted; D010363:Pattern Recognition, Automated / Q000379:methods*