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Coevolution and Linear Genetic Programming for Visual Learning

  • Krzysztof Krawiec
  • Bir Bhanu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2723)

Abstract

In this paper, a novel genetically-inspired visual learning method is proposed. Given the training images, this general approach induces a sophisticated feature-based recognition system, by using cooperative coevolution and linear genetic programming for the procedural representation of feature extraction agents. The paper describes the learning algorithm and provides a firm rationale for its design. An extensive experimental evaluation, on the demanding real-world task of object recognition in synthetic aperture radar (SAR) imagery, shows the competitiveness of the proposed approach with human-designed recognition systems.

Keywords

Object Recognition Recognition System Receiver Operating Characteristic Training Image Synthetic Aperture Radar 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Krzysztof Krawiec
    • 1
  • Bir Bhanu
    • 1
  1. 1.Center for Research in Intelligent SystemsUniversity of CaliforniaRiversideUSA

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