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Using neural networks to learn shape decomposition by successive prototypication

  • Nicholas Walker
Posters
Part of the Lecture Notes in Computer Science book series (LNCS, volume 427)

Abstract

I describe a neural-network which decomposes a set of inputs into a sequence of generative parameters. It uses a series of coupled parameter finding and removing networks and requires the input to be in a particular temporal format.

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References

  1. 1.
    Kohonen T. (1984). "Self organisation and Associative memory". Springer Verlag, Berlin 1984.Google Scholar
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    Saund E. (1989). "Dimensionality Reduction using Connectionist Networks". IEEE PAMI Vol 11 No 3, pp 304–314.Google Scholar
  3. 3.
    Leyton M. (1985). "Generative Systems of Analysers". Computer Vision, Graphics and Image Processing 31, pp 201–241.Google Scholar
  4. 4.
    Zipser D. and Anderson R.A. (1988). "A back-Propagation Programmed Network that Simulates Response Properties of a Subset of Posterior Parietal Neurons". Nature Vol 331, pp 679–684.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1990

Authors and Affiliations

  • Nicholas Walker
    • 1
  1. 1.Imperial Cancer Research Fund LaboratoriesLondon

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