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Remote Sensing Image Classification Algorithm Based on Hopfield Neural Network

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

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

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Abstract

Considering the feature of remote sensing images, we put forward a remote sensing image classification algorithm based on Hopfield neural network. First, the function and principle of Hopfield neural network is described in this paper. Then based on the common model of Hopfield neural network, the image classification algorithm using Hopfield neural network is realized and experimental results show that its precision is superior to that of the conventional maximum likelihood classification algorithm.

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Author information

Authors and Affiliations

  1. Information Engineering University Institute of Surveying and Mapping, Postfach 66, 450052, Zhengzhou, China

    Guang-jun Dong, Yong-sheng Zhang & Chao-jie Zhu

Authors
  1. Guang-jun Dong
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  2. Yong-sheng Zhang
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  3. Chao-jie Zhu
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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

Dong, Gj., Zhang, Ys., Zhu, Cj. (2006). Remote Sensing Image Classification Algorithm Based on Hopfield Neural Network. 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_49

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  • DOI: https://doi.org/10.1007/11760023_49

  • 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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