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    政大典藏 > College of Commerce > Department of MIS > Theses >  Item 140.119/87347


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/87347


    Title: 非監督式新細胞認知機神經網路之研究
    Studies on the Unsupervised Neocognitron
    Authors: 陳彥勳
    Chen, Yen-Shiun
    Contributors: 蔡瑞煌
    Tsaih, Ray-R.
    陳彥勳
    Chen, Yen-Shiun
    Keywords: 神經網路
    非監督式學習
    新細胞認知機
    印刷體中文字辨識
    Neural network
    Unsupervised learning
    Neocognition
    Printed chinese character recognition
    Date: 1996
    Issue Date: 2016-04-28 11:55:10 (UTC+8)
    Abstract: 本論文使用非監督式新細胞認知機（Unsupervised neocognitron）神經網路來便是印刷體中文字。
    In this study, we are investigating the feasibility of applying the unsupervised neocognitron to the recognition of printed Chinese characters.
    Reference: [1] K. Fukushima, "Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position", BioI Cybern., Vo1.36, pp .193-202,Apr. 1980.
    [2] Y. LeCun, B. Boser, "Backpropagation Applied to Handwritten Zip Code Recognition", Neural Computation, 1, pp.541-551, 1989.
    [3] H.Y. Liao, IS. Huang, and S.T. Huang, "Two-Dimentional Neural Networks for Handwritten Chinese Character Recognition", 1992 IEEE IJCNN illS79-S84.
    [4] A. Rajavelu, M.T. Musavi, and M.V. Shirvaikar, "A Neural Network Approach to Character Recognition", Neural Networks, Vol 2, pp.387-393 1989.
    [5] K. Fukushima, S. Miyake, T. Ito, "Neocognitron: A Neural Network Model for a Mechanism of Visual Pattern Recognition", IEEE Trans. on System, Man, and Cybernetics, Vol. SMC-13,No.S, Sep/Oct 1983. pp.826-834.
    [6] K. Fukushima, "Neocognitron: A Hierarchical Neural Network Capable of Visual Pattem Recognition", Neural Networks, Vol.1, pp.1l9-130, 1988.
    [7] K. Fukushima, N. Wake, "Handwdtten Alphanumeric Character Recognition by the
    Neocognitron", IEEE Trans. Oll Neural Networks, Vol.2, No.3, May 1991, pp.35S-36S.
    [8] K. Fukushima, Sei Miyake, "Neocognitron: A New Algorithm For Pattern Recognition Tolerant of Deformation and Shifts In Position", Pattem Recognition, Vol.lS, No.6, pp. 4SS-469,1982.
    [9] K. Fukushima, N. Wake, "Improved Neocognitroll with Bend-Detecting Cells", Proc. IEEE IJCNN, Vol.4, pp.190-19S, 1992.
    [10] K. Fukushima, "Analysis of the Process of Visual Pattem Recognition by the Neocognitron",Neural Networks, Vol. 2, pp.413-420, 1989.
    [11] MuraU M. Menon,Karl G. Heinemann, "Classification of Patterns Using a Self-Organizing Neural Network.", Neural Networks, Vol I, pp.201-21S, 1988.
    [12] Glenn S. Himes and Rafael M. Inigo, "Automatic Target Recognition Using a Neocognitron",IEEE Trans. on Knowledge and Data Engineering, Vol.4, No.2, April 1992.
    [13] James A. Freeman, "Neural Networks, Algorit~ Applications, and Program.rrring Techniquesll,Addison-Wesley Publishing Company, July 1992.
    [14] Hubel, D.H.,Wiesel, T.N.,”Receptive fields, binocular interaction and functional architecture in cat`s visual cortexll, 1. Physiol. 160, pp.l06-1S4, 1962.
    [IS] Hubel, D.H.,Wiesel, T.N.,"Receptive fields and functional architecture in two nonstriate visual area (18 and 19) of the catll, 1. Neurophysiol. 28,229-289, 1965.
    [16] Eun Jin Kim, "Handwritten Hangul Recognition Using a Modified Neocognitron", Neural Networks, Vol 4, pp.743-7S0, 1991.
    [17] S. Yamaguchi, H. Itakura, "A Car Detection System Using the Neocognitron", Proc. IEEE IJCNN, Vol.2, pp.1208-1213, 1991.
    [18] S.D. Wang, C.C. Pan, "A Neural Network Approach for Chinese Character Recognition", Proc.IEEE IJCNN, Vol.1, pp.416-419, 1990.
    [19] F.G. Shieh, “Studies of the Recognition of the Printed Chinese Character Using the
    NeocognitfOn model with the Changjei Codes", Master thesis of Computer and Information Engineering, Tatung Institute of Engineering, July 1993.
    Description: 碩士
    國立政治大學
    資訊管理學系
    83356004
    Source URI: http://thesis.lib.nccu.edu.tw/record/#B2002002866
    Data Type: thesis
    Appears in Collections:[Department of MIS] Theses

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