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
Link To Document :
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