Multiclass Object Classification Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4496

  author =       "Mengjie Zhang and Will Smart",
  title =        "Multiclass Object Classification Using Genetic
  institution =  "Computer Science, Victoria University of Wellington",
  year =         "2004",
  number =       "CS-TR-04-2",
  address =      "New Zealand",
  keywords =     "genetic algorithms, genetic programming, dynamic class
                 boundary determination, object recognition",
  URL =          "",
  URL =          "",
  abstract =     "genetic programming for multi-class object
                 classification problems. Rather than using fixed static
                 thresholds as boundaries to distinguish between
                 different classes, this approach introduces two methods
                 of classification where the boundaries between
                 different classes can be dynamically determined during
                 the evolutionary process. The two methods are centred
                 dynamic class boundary determination and slotted
                 dynamic class boundary determination. The two methods
                 are tested on four object classification problems of
                 increasing difficulty and are compared with the
                 commonly used static class boundary method. The results
                 suggest that, while the static class boundary method
                 works well on relatively easy object classification
                 problems, the two dynamic class boundary determination
                 methods outperform the static method for more
                 difficult, multiple class object classification
  size =         "15 pages",

Genetic Programming entries for Mengjie Zhang Will Smart