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A Neural Network Based on Biological Vision Learning and Its Application on Robot

  • Ying Gao
  • Xiaodan Lu
  • Liming Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3498)

Abstract

This paper proposes a neural network called “Hierarchical Overlapping Sensory Mapping (HOSM)”, motivated by the structure of receptive fields in biological vision. To extract the features from these receptive fields, a method called Candid covariance-free Incremental Principal Component Analysis (CCIPCA) is used to automatically develop a set of orthogonal filters. An application of HOSM on a robot with eyes shows that the HOSM algorithm can pay attention to different targets and get its cognition for different environments in real time.

Keywords

Neural Network Receptive Field Input Image Training Phase Video Frame 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    Hubel, D., Wiesel, T.: Receptive Fields, Binocular Interaction and Functional Architecture in the Cat. s Visual Cortex. J. of Physiology 160, 106–154 (1962)Google Scholar
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    Shou, T.: Brian Mechanisms of Visual Information Processing. Shanghai Science and Education Publishing House (1977)Google Scholar
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    Zhang, N., Weng, J., Zhang, Z.: A Developing Sensory Mapping for Robots. In: Development and Learning, 2002. Proceedings of the 2nd International Conference, June 12-15, pp. 13–20 (2002)Google Scholar
  4. 4.
    Weng, J., Zhang, Y., Hwang, W.S.: Candid Covariance-free Incremental Principal Component Analysis. IEEE Trans. Pattern Analysis and Machine Intelligence 25, 1034–1040 (2003)CrossRefGoogle Scholar
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    Hwang, W.-S., Weng, J.: Hierarchical Discriminant Regression. IEEE Trans. on Pattern Analysis and Machine Intelligence 22, 1277–1293 (2000)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Ying Gao
    • 1
  • Xiaodan Lu
    • 1
  • Liming Zhang
    • 1
  1. 1.Dept. Electronic EngineeringFudan UniversityShanghaiChina

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