• DocumentCode
    296023
  • Title

    Self-organising learning of receptive fields in multi-resolution

  • Author

    Deng, D. ; Chan, K.P. ; Yu, Y.L.

  • Author_Institution
    Inst. of Radio Eng. & Autom., South China Univ. of Technol., Guangzhou, China
  • Volume
    5
  • fYear
    1995
  • fDate
    Nov/Dec 1995
  • Firstpage
    2831
  • Abstract
    The statistical likelihood of Gabor filters and primary visual cortex has been of interest for years, yet learning mechanisms proposed did not generate satisfactory Gabor-like receptive fields. In this paper, a new computational model of self-organised Hebbian learning (SOHL) is proposed to work on a multi-resolution image pyramid for the problem of visual receptive field learning. Receptive fields of both orientation and spatial frequency selectivity are observed in the authors´ simulation result
  • Keywords
    Hebbian learning; image resolution; physiological models; self-organising feature maps; spatial filters; visual perception; Gabor filters; multi-resolution image pyramid; primary visual cortex; receptive fields; self-organised Hebbian learning; statistical likelihood; visual receptive field learning; Biological system modeling; Brain modeling; Computational modeling; Computer science; Cost function; Gabor filters; Hebbian theory; Learning systems; Radio frequency; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1995. Proceedings., IEEE International Conference on
  • Conference_Location
    Perth, WA
  • Print_ISBN
    0-7803-2768-3
  • Type

    conf

  • DOI
    10.1109/ICNN.1995.488182
  • Filename
    488182