• DocumentCode
    288886
  • Title

    Invariant image recognition using triple correlations and neural networks

  • Author

    Tiraki, A. ; Delopoulos, A. ; Kollias, S.

  • Author_Institution
    Div. of Comput. Sci., Nat. Tech. Univ. of Athens, Greece
  • Volume
    6
  • fYear
    1994
  • fDate
    27 Jun- 2 Jul 1994
  • Firstpage
    4055
  • Abstract
    Triple-correlation-based image representations were previously (Delopoulos, Tirakis, and Kollias, 1994) combined with neural network architectures for deriving an invariant, with respect to translation, rotation and dilation, robust classification scheme. Efficient implementations are described in this paper, which reduce the computational complexity of the method. Hierarchical, multiresolution neural networks are proposed as an effective architecture for achieving this purpose
  • Keywords
    computational complexity; image recognition; image representation; neural nets; computational complexity; hierarchical multiresolution neural networks; invariant image recognition; neural network architectures; triple correlations; Computer architecture; Feature extraction; Higher order statistics; Image recognition; Image representation; Neural networks; Retina; Robustness; Signal resolution; Statistical distributions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-1901-X
  • Type

    conf

  • DOI
    10.1109/ICNN.1994.374863
  • Filename
    374863