Genetic Programming for Object Detection: Improving Fitness Functions and Optimising Training Data

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Zhang:2006:IIIB,
  author =       "Mengjie Zhang and Malcolm Lett",
  title =        "Genetic Programming for Object Detection: Improving
                 Fitness Functions and Optimising Training Data",
  journal =      "The IEEE Intelligent Informatics Bulletin",
  year =         "2006",
  volume =       "7",
  number =       "1",
  pages =        "12--21",
  month =        dec,
  keywords =     "genetic algorithms, genetic programming, object
                 detection, object localisation, object recognition,
                 object classification, evolutionary computing, fitness
                 function, training data",
  ISSN =         "1727-5997",
  URL =          "http://www.comp.hkbu.edu.hk/~cib/2006/Dec/iib_vol7no1_article2.pdf",
  size =         "10 pages",
  abstract =     "This paper describes an approach to the improvement of
                 a fitness function and the optimisation of training
                 data in genetic programming (GP) for object detection
                 particularly object localisation problems. The fitness
                 function uses the weighted F-measure of a genetic
                 program and considers the localisation fitness values
                 of the detected object locations. To investigate the
                 training data with this fitness function, we categorise
                 the training data into four types: exact centre, close
                 to centre, include centre, and background. The approach
                 is examined and compared with an existing fitness
                 function on three object detection problems of
                 increasing difficulty. The results suggest that the new
                 fitness function outperforms the old one by producing
                 far fewer false alarms and spending much less training
                 time and that the first two types of the training
                 examples contain most of the useful information for
                 object detection. The results also suggest that the
                 complete background type of data can be removed from
                 the training set.",
  notes =        "formerly IEEE Computational Intelligence Bulletin)",
}

Genetic Programming entries for Mengjie Zhang Malcolm Lett

Citations