• DocumentCode
    2968964
  • Title

    Artificial neural networks which can see geometric illusions in human vision

  • Author

    Chao, Jinhui ; Kishigami, Tohru ; Minowa, Kenji ; Tsujii, Shigeo

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Chuo Univ., Tokyo, Japan
  • Volume
    3
  • fYear
    1993
  • fDate
    25-29 Oct. 1993
  • Firstpage
    2209
  • Abstract
    A new physiological model is proposed for geometrical illusion phenomena in human vision and is implemented by artificial neural networks. According to the model, illusion is a result of nonuniform bending in visual space whose Riemannian metric tensor is determined by lateral excitatory-inhibitory dynamics of the retina neurons.
  • Keywords
    neural nets; neurophysiology; physiological models; visual perception; Riemannian metric tensor; geometric illusions; human vision; lateral excitatory-inhibitory dynamics; neural networks; physiological model; retina neurons; visual space; Artificial neural networks; Chaos; Humans; Information processing; Intelligent networks; Neurons; Psychology; Solid modeling; Space technology; Tensile stress;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
  • Print_ISBN
    0-7803-1421-2
  • Type

    conf

  • DOI
    10.1109/IJCNN.1993.714165
  • Filename
    714165