A Relevance Feedback Method based on Genetic Programming for Classification of Remote Sensing Images
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @Article{Santos2010,
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author = "J. A. {dos Santos} and C. D. Ferreira and
R. {da S. Torres} and M. A. Goncalves and R. A. C. Lamparelli",
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title = "A Relevance Feedback Method based on Genetic
Programming for Classification of Remote Sensing
Images",
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journal = "Information Sciences",
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year = "2011",
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volume = "181",
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number = "12",
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pages = "2671--2684",
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month = "1 " # jul,
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keywords = "genetic algorithms, genetic programming, content-based
image retrieval, region descriptors, relevance
feedback, remote sensing image classification",
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ISSN = "0020-0255",
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annote = "The Pennsylvania State University CiteSeerX Archives",
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bibsource = "OAI-PMH server at citeseerx.ist.psu.edu",
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language = "en",
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oai = "oai:CiteSeerX.psu:10.1.1.460.574",
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rights = "Metadata may be used without restrictions as long as
the oai identifier remains attached to it.",
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DOI = "doi:10.1016/j.ins.2010.02.003",
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URL = "http://www.sciencedirect.com/science/article/B6V0C-4YBMF9K-2/2/7be908a0802e1675ad8e8258bfbc4e01",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.460.574",
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URL = "http://www.ic.unicamp.br/~jsantos/pdf/santos2011is.pdf",
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size = "14 pages",
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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