Feature extraction from multiple data sources using genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "John J. Szymanski and Steven P. Brumby and 
                 Paul Pope and Damian Eads and Diana Esch-Mosher and 
                 Mark Galassi and Neal R. Harvey and Hersey D. W. McCulloch and 
                 Simon J. Perkins and Reid Porter and James Theiler and 
                 A. Cody Young and Jeffrey J. Bloch and Nancy David",
  title =        "Feature extraction from multiple data sources using
                 genetic programming",
  booktitle =    "Algorithms and Technologies for Multispectral,
                 Hyperspectral, and Ultraspectral Imagery VIII",
  year =         "2002",
  editor =       "Sylvia S. Shen and Paul E. Lewis",
  volume =       "4725",
  series =       "SPIE",
  pages =        "338--345",
  month =        aug,
  organisation = "SPIE--The International Society for Optical
  keywords =     "genetic algorithms, genetic programming, Multispectral
                 analysis, image processing, evolutionary computation,
                 feature extractionn",
  URL =          "http://www.cs.rit.edu/~dre9227/papers/szymanskiSPIE4725.pdf",
  broken =       "http://spie.org/scripts/abstract.pl?bibcode=2002SPIE%2e4725%2e%2e338S&db_key=INST&qs=spie&s_type=",
  broken =       "http://citeseer.nj.nec.com/szymanski02feature.html",
  URL =          "http://citeseer.ist.psu.edu/540967.html",
  DOI =          "doi:10.1117/12.478765",
  size =         "8 pages",
  abstract =     "Feature extraction from imagery is an important and
                 long-standing problem in remote sensing. In this paper,
                 we report on work using genetic programming to perform
                 feature extraction simultaneously from multispectral
                 and digital elevation model (DEM) data. We use the
                 GENetic Imagery Exploitation (GENIE) software for this
                 purpose, which produces image-processing software that
                 inherently combines spatial and spectral processing.
                 GENIE is particularly useful in exploratory studies of
                 imagery, such as one often does in combining data from
                 multiple sources. The user trains the software by
                 painting the feature of interest with a simple
                 graphical user interface. GENIE then uses genetic
                 programming techniques to produce an image-processing
                 pipeline. Here, we demonstrate evolution of image
                 processing algorithms that extract a range of land
                 cover features including towns, wildfire burnscars, and
                 forest. We use imagery from the DOE/NNSA Multispectral
                 Thermal Imager (MTI) spacecraft, fused with USGS
                 1:24000 scale DEM data.",
  notes =        "also appears as oai:CiteSeerPSU:540967 but given
                 different authors!",

Genetic Programming entries for John J Szymanski Steven P Brumby Paul Pope Damian Eads Diana Esch-Mosher Mark Galassi Neal R Harvey Hersey D W McCulloch Simon Perkins Reid B Porter James Theiler A Cody Young Jeffrey J Bloch Nancy David