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Topographic Map Object Classification Using Real-Value Grammar Classifier System

  • Lukasz Cielecki
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7143)

Abstract

Learning Classifier Systems (LCS) became a large branch of machine learning applications that received a lot of attention recently. Our model of LCS - rGCS or real-value Grammar Classifier System - uses grammar inference to classify real-value vectors which may describe range variety of problems. In this paper we utilize the rGCS core in an object recognition task. Our application seeks for certain graphic symbols on a topographic map scan.

Keywords

Input Space Context Free Grammar Object Recognition Task Terminal Symbol Kohonen Neural Network 
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 2012

Authors and Affiliations

  • Lukasz Cielecki
    • 1
  1. 1.Institute of Computer Engineering, Control and RoboticsWroclaw University of TechnologyWroclawPoland

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