• DocumentCode
    1747184
  • Title

    CNN-based modeling of the human early vision system

  • Author

    Chae, Seung-Pyo ; Lee, Jeong-Woo ; Kim, Myoung-Nam ; Kim, Si-Yeol ; Cho, Jin-Ho

  • Author_Institution
    Sch. of Electron. & Electr. Eng., Kyungpook Nat. Univ., Taegu, South Korea
  • Volume
    1
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    192
  • Abstract
    CNN (cellular neural network)-based retina model is introduced to simulate the human early vision system. By considering the retinal activity using CNN, we can begin to think about whole retinal interactions in space/time and consider the mechanism of a large population of cells as the edge detection and detection of moving stimuli. Furthermore, after simulating the output response of each retinal neuron, ERG, which is volume conductor potential recorded at the cornea and used as important diagnostic measure in eye clinic, is calculated. Each wavelet which composes the typical ERG has close relationship with the mechanism of a special retinal layer and by analyzing the each wavelet form we can guess the clinical state of special retinal layer
  • Keywords
    cellular biophysics; cellular neural nets; edge detection; electroretinography; image motion analysis; medical signal processing; patient diagnosis; visual evoked potentials; wavelet transforms; CNN-based retina model; ERG; cellular neural network; cornea; diagnostic measure; edge detection; eye clinic; human early vision system; moving stimuli; output response; retinal activity; retinal interactions; retinal neuron; special retinal layer; volume conductor potential; wavelet; Cellular networks; Cellular neural networks; Conductors; Humans; Image edge detection; Machine vision; Neural networks; Neurons; Retina; Wavelet analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics, 2001. Proceedings. ISIE 2001. IEEE International Symposium on
  • Conference_Location
    Pusan
  • Print_ISBN
    0-7803-7090-2
  • Type

    conf

  • DOI
    10.1109/ISIE.2001.931780
  • Filename
    931780