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A distributed classifier based on Yprel networks cooperation

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From Natural to Artificial Neural Computation (IWANN 1995)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 930))

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Abstract

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: (i) an Yprel classifier is a set of Yprels networks, each network being associated with a particular class; (ii) the learning is supervised and conducted class by class; (iii) the structure of the network is not a priori chosen, but is determined step by step during the learning process; (iv) the learning process is incremental: each network improves its own learning base with the errors of the previous test; (v) networks cooperate: each network can use the outputs of the previously builded networks. Preliminary results are given on a well-known classification task (recognition of typographic characters).

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Authors and Affiliations

  1. La3i UFR des Sciences et Techniques, Université de Rouen, F-76821, Mont Saint Aignan Cedex, France

    Emmanuel Stocker, Yves Lecourtier & Abdel Ennaji

Authors
  1. Emmanuel Stocker
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  2. Yves Lecourtier
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  3. Abdel Ennaji
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Editor information

José Mira Francisco Sandoval

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© 1995 Springer-Verlag Berlin Heidelberg

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Stocker, E., Lecourtier, Y., Ennaji, A. (1995). A distributed classifier based on Yprel networks cooperation. In: Mira, J., Sandoval, F. (eds) From Natural to Artificial Neural Computation. IWANN 1995. Lecture Notes in Computer Science, vol 930. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-59497-3_193

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  • DOI: https://doi.org/10.1007/3-540-59497-3_193

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-59497-0

  • Online ISBN: 978-3-540-49288-7

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