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International Symposium on Neural Networks

ISNN 2006: Advances in Neural Networks - ISNN 2006 pp 93–97Cite as

Face Recognition Using a Neural Network Simulating Olfactory Systems

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3972))

Abstract

A novel chaotic neural network K-set has been constructed based in research on biological olfactory systems. This non-convergent neural network simulates the capacities of biological brains for signal processing in pattern recognition. Its accuracy and efficiency are demonstrated in this report on an application to human face recognition, with comparisons of performance with conventional pattern recognition algorithms.

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References

  1. Freeman, W.J., Kozma, R.: Biocomplexity: Adaptive Behavior in Complex Stochastic Dynamic Systems. Biosystems 59, 109–123 (2001)

    Article  Google Scholar 

  2. Li, G., Lou, Z., Wang, L., Li, X., Freeman, W.J.: Application of Chaotic Neural Model Based on Olfactory System on Pattern Recognitions. In: Wang, L., Chen, K., Ong, Y. S. (eds.) ICNC 2005. LNCS, vol. 3610, pp. 378–381. Springer, Heidelberg (2005)

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  3. Pan, Z., Adams, R., Bolouri, H.: Dimensionality Reduction of Face Images Using Discrete Cosine Transforms for Recognition. IEEE Conference on Computer Vision and Pattern Recognition (2000)

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  4. Samaria, F.: Face Recognition Using Hidden Markov Models, PhD Thesis, Cambridge University (1994)

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Author information

Authors and Affiliations

  1. National Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, 310027, China

    Guang Li

  2. Department of Biomedical Engineering, Zhejiang University, Hangzhou, 310027, China

    Jin Zhang & You Wang

  3. Software College, Human University, Changsha, 410082, China

    Jin Zhang

  4. Division of Neurobiology, University of California at Berkeley, Donner 101, Berkeley, CA, 94720-3206, USA

    Walter J. Freeman

Authors
  1. Guang Li
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  2. Jin Zhang
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  3. You Wang
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  4. Walter J. Freeman
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Li, G., Zhang, J., Wang, Y., Freeman, W.J. (2006). Face Recognition Using a Neural Network Simulating Olfactory Systems. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_14

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  • DOI: https://doi.org/10.1007/11760023_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34437-7

  • Online ISBN: 978-3-540-34438-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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