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Evolving Visual Feature Detectors

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 1674)

Abstract

This paper describes the generation and selection of visual feature detectors. The feature detectors are randomly generated, and are built out of components, some having functionality inspired on observations of animal visual pathways. The input for the feature detectors consists of non-synthetic images, while the selectionist pressure comes from the amount of information the feature detectors generate. The experimental setup is described and some results are given.

Keywords

  • Feature Detector
  • Processing Pathway
  • Scalar Scalar
  • Monkey Striate Cortex
  • Experimental Setup Type

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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  • DOI: 10.1007/3-540-48304-7_34
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References

  1. T. Belpaeme. Evolution of visual feature detectors. In S. Cagnoni and P. Nordin, editors, Proceedings of EvoIASP99, Late breaking papers, 1999.

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© 1999 Springer-Verlag Berlin Heidelberg

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Belpaeme, T. (1999). Evolving Visual Feature Detectors. In: Floreano, D., Nicoud, JD., Mondada, F. (eds) Advances in Artificial Life. ECAL 1999. Lecture Notes in Computer Science(), vol 1674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48304-7_34

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  • DOI: https://doi.org/10.1007/3-540-48304-7_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66452-9

  • Online ISBN: 978-3-540-48304-5

  • eBook Packages: Springer Book Archive