Algorithm Discovery Using the Genetic Programming Paradigm: Extracting Low-Contrast Curvilinear Features from SAR Images of Arctic Ice
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @InCollection{daida:1996:aigp2,
-
author = "Jason M. Daida and Jonathan D. Hommes and
Tommaso F. Bersano-Begey and Steven J. Ross and John F. Vesecky",
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title = "Algorithm Discovery Using the Genetic Programming
Paradigm: Extracting Low-Contrast Curvilinear Features
from {SAR} Images of Arctic Ice",
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booktitle = "Advances in Genetic Programming 2",
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publisher = "MIT Press",
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year = "1996",
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editor = "Peter J. Angeline and K. E. {Kinnear, Jr.}",
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pages = "417--442",
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chapter = "21",
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address = "Cambridge, MA, USA",
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keywords = "genetic algorithms, genetic programming, GAIA",
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ISBN = "0-262-01158-1",
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URL = "http://sitemaker.umich.edu/daida/files/GP2_cha21.pdf",
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URL = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6277526",
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DOI = "doi:10.7551/mitpress/1109.003.0028",
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size = "26 pages",
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abstract = "We discuss the application of genetic programming (GP)
to image analysis problems in geoscience and remote
sensing and describes how a GP can be adapted for
processing large data sets (in our case, 1024 x 1024
pixel images plus texture channels). The featured
problem is one that has not been adequately solved for
this type of imagery. We describe the placement of GP
in the overall scheme of algorithm discovery in
geoscience image analysis and describe how GP
complements a scientist's hypothesis-test derivation of
such algorithms. The featured solution consists of a
standard non-ADF GP that incorporates a dynamic fitness
function.",
-
notes = "see also
http://www.sprl.umich.edu/acers/gaia/aigpGaia.html",
- }
Genetic Programming entries for
Jason M Daida
Jonathan D Hommes
Tommaso F Bersano-Begey
Steven J Ross
John F Vesecky
Citations