New Fitness Functions in Genetic Programming for Object Detection

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Malcolm Lett and Mengjie Zhang",
  title =        "New Fitness Functions in Genetic Programming for
                 Object Detection",
  booktitle =    "Proceeding of Image and Vision Computing International
  year =         "2004",
  editor =       "David Pairman and Heather North and Stephen McNeill",
  pages =        "441--446",
  month =        nov,
  publisher =    "Lincoln, Landcare Research",
  address =      "Akaroa, New Zealand",
  keywords =     "genetic algorithms, genetic programming, object
                 detection, object localisation, fitness function",
  URL =          "",
  size =         "6 pages",
  abstract =     "Object detection is an important field of research in
                 computer vision which genetic programming has been
                 applied to recently. This paper describes two new
                 fitness functions in genetic programming for object
                 detection. Both fitness functions are based on recall
                 and precision of genetic programs. The first is a
                 tolerance based fitness function and the second is a
                 weighted fitness function. The merits and effectiveness
                 of the two fitness function are discussed. The two
                 fitness functions are examined and compared on three
                 object detection problems of increasing dificulty. The
                 results suggest that both fitness functions perform
                 very well on the relatively easy problem, the weighted
                 fitness function outperforms the tolerance based
                 fitness function on the relatively dificult problems.",
  notes =        "see also \cite{vuw-CS-TR-04-12} \cite{Lett:BSc}
                 broken Mar 2018)

                 Fri, 02 Jun 2006 17:03:20 +0800 IVCNZ",

Genetic Programming entries for Malcolm Lett Mengjie Zhang