Comparison of GENIE and conventional supervised classifiers for multispectral image feature extraction

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

@Article{oai:CiteSeerPSU:561309,
  author =       "Neal R. Harvey and James Theiler and 
                 Steven P. Brumby and Simon Perkins and John J. Szymanski and 
                 Jeffrey J. Bloch and Reid B. Porter and Mark Galassi and 
                 A. Cody Young",
  title =        "Comparison of {GENIE} and conventional supervised
                 classifiers for multispectral image feature
                 extraction",
  journal =      "IEEE Transactions on Geoscience and Remote Sensing",
  year =         "2002",
  volume =       "40",
  number =       "2",
  pages =        "393--404",
  month =        feb,
  keywords =     "genetic algorithms, genetic programming, Supervised
                 Classification, Image Processing, Evolutionary
                 Algorithms, Multispectral Imagery, Remote Sensing,
                 feature extraction, geophysical signal processing,
                 geophysical techniques, geophysics computing, image
                 classification, multidimensional signal processing,
                 terrain mapping, GENIE, GENetic Imagery Exploitation,
                 IR, feature extraction, geophysical measurement
                 technique, hybrid evolutionary algorithm, image
                 classification, image processing, infrared, land
                 surface, multispectral remote sensing, supervised
                 classifier, terrain mapping, visible",
  ISSN =         "0196-2892",
  URL =          "http://nis-www.lanl.gov/~simes/webdocs/harveyIEEE_TGARS2001.pdf",
  URL =          "http://citeseer.ist.psu.edu/561309.html",
  size =         "12 pages",
  abstract =     "We have developed an automated feature detection/
                 classification system, called Genie (GENetic Imagery
                 Exploitation), which has been designed to generate
                 image processing pipelines for a variety of feature
                 detection/ classification tasks. Genie is a hybrid
                 evolutionary algorithm that addresses the general
                 problem of finding features of interest in
                 multi-spectral remotely-sensed images. We describe our
                 system in detail together with experiments involving
                 comparisons of Genie with several conventional
                 supervised classification techniques, for a number of
                 classification tasks using multi-spectral
                 remotely-sensed imagery.",
  notes =        "On line version not identical to IEEE version

                 Inspec Accession Number: 7265352, CODEN: IGRSD2",
}

Genetic Programming entries for Neal R Harvey James Theiler Steven P Brumby Simon Perkins John J Szymanski Jeffrey J Bloch Reid B Porter Mark Galassi A Cody Young

Citations