• DocumentCode
    1568632
  • Title

    An automatic tool to design CNN-UM programs

  • Author

    Pazienza, Giovanni E. ; Karacs, Kristof

  • Author_Institution
    Vilasis-Cardona Eng. i Arquitectura La Salle, Univ. Ramon Llull, Barcelona
  • fYear
    2007
  • Firstpage
    492
  • Lastpage
    495
  • Abstract
    Programs for the Cellular Neural Network - Universal Machine are usually designed explicitly, and there is no method to create them automatically. In this paper we present a tool, based on a genetic approach, capable of determining what CNN templates compose a CNN-UM program performing a given image processing task, and in which order they must be applied to the input. The effectiveness of our system is demonstrated experimentally on real-life problems, like the route number detection on public transport vehicles.
  • Keywords
    cellular neural nets; digital signal processing chips; image processing; neural chips; CNN-UM program; automatic tool; cellular neural network universal machine; genetic approach; image processing task; Algorithm design and analysis; Analog computers; Binary trees; Cellular neural networks; Computer networks; Genetics; Image processing; Turing machines; Vehicle detection; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuit Theory and Design, 2007. ECCTD 2007. 18th European Conference on
  • Conference_Location
    Seville
  • Print_ISBN
    978-1-4244-1341-6
  • Electronic_ISBN
    978-1-4244-1342-3
  • Type

    conf

  • DOI
    10.1109/ECCTD.2007.4529640
  • Filename
    4529640