• DocumentCode
    2534766
  • Title

    A programmable vision chip for CNN based algorithms

  • Author

    Dupret, A. ; Klein, J.O. ; Nshare, A.

  • Author_Institution
    Inst. d´´Electron. Fondamentale, Univ. de Paris-Sud, Orsay, France
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    207
  • Lastpage
    212
  • Abstract
    In this paper, an original architecture of cellular neural network (CNN) vision chip is addressed. In the introduction, an analyse of the limitations of the usual approaches leads us to propose an original architecture. The paper is dedicated to the description of the three main blocks of our vision chip. Then, the major building blocks are detailed. Finally, design considerations and the practical implementation of a typical CNN algorithm are discussed
  • Keywords
    cellular neural nets; computer vision; convolution; mixed analogue-digital integrated circuits; neural net architecture; cellular neural network; convolution; digital analog processor; neural net architecture; programmable vision chip; Algorithm design and analysis; Buildings; Cellular neural networks; Circuits; Computer architecture; Concurrent computing; Image processing; Moore´s Law; Parallel processing; Retina;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and Their Applications, 2000. (CNNA 2000). Proceedings of the 2000 6th IEEE International Workshop on
  • Conference_Location
    Catania
  • Print_ISBN
    0-7803-6344-2
  • Type

    conf

  • DOI
    10.1109/CNNA.2000.876846
  • Filename
    876846