A Relevance Feedback Method based on Genetic Programming for Classification of Remote Sensing Images

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

@Article{Santos2010,
  author =       "J. A. {dos Santos} and C. D. Ferreira and 
                 R. {da S. Torres} and M. A. Goncalves and R. A. C. Lamparelli",
  title =        "A Relevance Feedback Method based on Genetic
                 Programming for Classification of Remote Sensing
                 Images",
  journal =      "Information Sciences",
  year =         "2011",
  volume =       "181",
  number =       "12",
  pages =        "2671--2684",
  month =        "1 " # jul,
  keywords =     "genetic algorithms, genetic programming, content-based
                 image retrieval, region descriptors, relevance
                 feedback, remote sensing image classification",
  ISSN =         "0020-0255",
  annote =       "The Pennsylvania State University CiteSeerX Archives",
  bibsource =    "OAI-PMH server at citeseerx.ist.psu.edu",
  language =     "en",
  oai =          "oai:CiteSeerX.psu:10.1.1.460.574",
  rights =       "Metadata may be used without restrictions as long as
                 the oai identifier remains attached to it.",
  DOI =          "doi:10.1016/j.ins.2010.02.003",
  URL =          "http://www.sciencedirect.com/science/article/B6V0C-4YBMF9K-2/2/7be908a0802e1675ad8e8258bfbc4e01",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.460.574",
  URL =          "http://www.ic.unicamp.br/~jsantos/pdf/santos2011is.pdf",
  size =         "14 pages",
  abstract =     "This paper presents an interactive technique for
                 remote sensing image classification. In our proposal,
                 users are able to interact with the classification
                 system, indicating regions of interest (and those which
                 are not). This feedback information is employed by a
                 genetic programming approach to learning user
                 preferences and combining image region descriptors that
                 encode spectral and texture properties. Experiments
                 demonstrate that the proposed method is effective for
                 image classification tasks and outperforms the
                 traditional MaxVer method.",
}

Genetic Programming entries for Jefersson Alex dos Santos Cristiano Dalmaschio Ferreira Ricardo da Silva Torres Marcos Andre Goncalves Rubens Augusto Camargo Lamparelli

Citations