title: The labeled systems of multiple neural networks.
abstract: This paper proposes an implementation scheme of K-class classification problem using systems of multiple neural networks. Usually, a multi-class problem is decomposed into simple sub-problems solved independently using similar single neural networks. For the reason that these sub-problems are not equivalent in their complexity, we propose a system that includes reinforced networks destined to solve complicated parts of the entire problem. Our approach is inspired from principles of the multi-classifiers systems and the labeled classification, which aims to improve performances of the networks trained by the Back-Propagation algorithm. We propose two implementation schemes based on both OAO (one-against-all) and OAA (one-against-one). The proposed models are evaluated using iris and human thigh databases.
authors.affiliation: LAIG, Université de Guelma, Algéria. nemissi_m@yahoo.fr
authors.forename: M
authors.initials: M
authors.lastname: Nemissi
authors.forename: H
authors.initials: H
authors.lastname: Seridi
authors.forename: H
authors.initials: H
authors.lastname: Akdag