• DocumentCode
    2899410
  • Title

    Image learning classifier system using genetic algorithms

  • Author

    McAulay, Alastair D. ; Oh, Jae Chan

  • Author_Institution
    Dept. of Comput. Sci., Wright State Univ., Dayton, OH, USA
  • fYear
    1989
  • fDate
    22-26 May 1989
  • Firstpage
    705
  • Abstract
    The authors examine aspects of machine learning by classifier systems that use genetic algorithms. In particular, adaptive image learning and classification are considered. Standard classifier systems are not well suited for seeking out multiple goals as is necessary in image learning and classification problems. To improve the performance of standard classifier systems for the image learning task, several modifications are suggested. The modifications result in a far better performance for classifier system on the ImageLearn domain
  • Keywords
    adaptive systems; computerised pattern recognition; computerised picture processing; knowledge representation; learning systems; neural nets; adaptive image learning; classification; genetic algorithms; image learning classifier; Adaptive systems; Computer science; Current measurement; Genetic algorithms; Humans; Image recognition; Learning systems; Machine learning; Particle measurements; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aerospace and Electronics Conference, 1989. NAECON 1989., Proceedings of the IEEE 1989 National
  • Conference_Location
    Dayton, OH
  • Type

    conf

  • DOI
    10.1109/NAECON.1989.40288
  • Filename
    40288