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ICANN 98 pp 755-760 | Cite as

Automatic neural generalized font identification

  • A. M. González
  • J. Dorronsoro
  • C. Santa Cruz
Conference paper
Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)

Abstract

Neural methods are gaining a steady acceptance as powerful tools in a variety of pattern detection problems, OCR certainly being one of them. The concrete implementation of these neural OCR systems is of course a well guarded corporate secret, but in broad terms it can be said that in most of the cases, multilayer perceptrons (MLPs) are used. There are several reasons for the MLPs’ success. To begin with, they are based in well understood mathematical and statistical principles and there are efficient tools and methodologies for their training and evaluation. Furthermore they have good generalization properties.

Keywords

Discrete Cosine Transform Radial Basis Function Network Inverse Discrete Cosine Transform Model Overfitting Good Generalization Property 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag London 1998

Authors and Affiliations

  • A. M. González
    • 1
  • J. Dorronsoro
    • 1
  • C. Santa Cruz
    • 1
  1. 1.Department of Computer Engineering and Instituto de Ingeniería del ConocimientoUniversidad Autónoma de MadridMadridSpain

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