Investigation of image feature extraction by a genetic algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Brumby:1999:SPIE,
  author =       "Steven P. Brumby and James Theiler and 
                 Simon J. Perkins and Neal Harvey and John J. Szymanski and 
                 Jeffrey J. Bloch and Melanie Mitchell",
  title =        "Investigation of image feature extraction by a genetic
                 algorithm",
  booktitle =    "Applications and Science of Neural Networks, Fuzzy
                 Systems, and Evolutionary Computation II, Proceedings
                 of SPIE",
  year =         "1999",
  editor =       "Bruno Bosacchi and David B. Fogel and 
                 James C. Bezdek",
  volume =       "3812",
  pages =        "24--31",
  month =        "19-20 " # jul,
  keywords =     "genetic algorithms, genetic programming, Evolutionary
                 computation, image analysis, multi-spectral analysis",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.8210",
  URL =          "http://web.cecs.pdx.edu/~mm/spie3812.pdf",
  DOI =          "doi:10.1117/12.367697",
  size =         "8 pages",
  abstract =     "We describe the implementation and performance of a
                 genetic algorithm (GA) which generates image feature
                 extraction algorithms for remote sensing applications.
                 We describe our basis set of primitive image operators
                 and present our chromosomal representation of a
                 complete algorithm. Our initial application has been
                 geospatial feature extraction using publicly available
                 multi-spectral aerial-photography data sets. We present
                 the preliminary results of our analysis of the
                 efficiency of the classic genetic operations of
                 crossover and mutation for our application, and discuss
                 our choice of evolutionary control parameters. We
                 exhibit some of our evolved algorithms, and discuss
                 possible avenues for future progress.",
  notes =        "Fixed length but includes NOP to give variable length
                 http://www.spie.org/web/meetings/programs/sd99/confs/3812.html
                 Los Alamos National Lab; Santa Fe Institute [3812-03]",
}

Genetic Programming entries for Steven P Brumby James Theiler Simon Perkins Neal R Harvey John J Szymanski Jeffrey J Bloch Melanie Mitchell

Citations