Anglais Applications of Evolutionary Computation in Image Processing and Pattern Recognition

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À propos

This book presents the use of efficient
Evolutionary Computation (EC) algorithms for solving diverse real-world image
processing and pattern recognition problems. It provides an overview of the
different aspects of evolutionary methods in order to enable the reader in
reaching a global understanding of the field and, in conducting studies on
specific evolutionary techniques that are related to applications in image
processing and pattern recognition. It explains the basic ideas of the proposed
applications in a way that can also be understood by readers outside of the
field. Image processing and pattern recognition practitioners who are not
evolutionary computation researchers will appreciate the discussed techniques
beyond simple theoretical tools since they have been adapted to solve
significant problems that commonly arise on such areas. On the other hand,
members of the evolutionary computation community can learn the way in which
image processing and pattern recognition problems can be translated into an
optimization task. The book has been structured so that each chapter can be
read independently from the others. It can serve as reference book for students
and researchers with basic knowledge in image processing and EC methods.


  • Auteur(s)

    Erik Cuevas, Daniel Zaldivar, Marco Perez-Cisneros

  • Éditeur

    Springer

  • Distributeur

    Numilog

  • Date de parution

    07/11/2015

  • EAN

    9783319264622

  • Disponibilité

    Disponible

  • Action copier/coller

    Dans le cadre de la copie privée

  • Nb pages copiables

    1

  • Action imprimer

    Dans le cadre de la copie privée

  • Nb pages imprimables

    1

  • Partage

    Dans le cadre de la copie privée

  • Nb Partage

    6 appareils

  • Poids

    8 284 Ko

  • Diffuseur

    Numilog

  • Entrepôt

    Numilog

  • Support principal

    ebook (ePub)

  • Version ePub

Aucune information sur l'accessibilité n'est disponible

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