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Incremental distributed classifier building

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4 Author(s)
Stocker, E. ; UFR des Sci. et Techniques, Rouen Univ., Mont-Saint-Aignan, France ; Ribert, A. ; Lecourtier, Y. ; Ennaji, A.

In this paper we present a scheme of classification based on a particular processing element (neuron) called yprel. The main characteristics of the approach are: (1) an yprel classifier is a set of yprels networks, each network being associated with a particular class; (2) the learning is supervised and conducted class by class; (3) the structure of the network is not a priori chosen, but is determined step by step during the learning process; (4) the learning process is incremental: each network improves its own learning base with the errors of the previous test; (5) networks cooperate: each network can use the outputs of the previously built networks. Preliminary results are given on a well-known classification task (recognition of typographic characters)

Published in:

Pattern Recognition, 1996., Proceedings of the 13th International Conference on  (Volume:4 )

Date of Conference:

25-29 Aug 1996