Classification of Spectral Imagery Using Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Rauss:2000:GECCO,
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author = "Patrick J. Rauss and Jason M. Daida and
Shahbaz Chaudhary",
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title = "Classification of Spectral Imagery Using Genetic
Programming",
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pages = "726--733",
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year = "2000",
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publisher = "Morgan Kaufmann",
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booktitle = "Proceedings of the Genetic and Evolutionary
Computation Conference (GECCO-2000)",
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editor = "Darrell Whitley and David Goldberg and
Erick Cantu-Paz and Lee Spector and Ian Parmee and Hans-Georg Beyer",
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address = "Las Vegas, Nevada, USA",
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publisher_address = "San Francisco, CA 94104, USA",
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month = "10-12 " # jul,
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keywords = "genetic algorithms, genetic programming",
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ISBN = "1-55860-708-0",
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URL = "http://gpbib.cs.ucl.ac.uk/gecco2000/RW157.pdf",
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size = "8 pages",
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abstract = "This paper describes an initial use of genetic
programming as a discovery engine that derives two sets
of information from hyper-spectral imagery. The first
consists of a set of classification algorithms learned
from the data. The second consists of reduced subsets
of the most germane bands for use in a given
classification, since not all spectral bands are of use
in deriving a particular classification algorithm.
Currently, there are only a few techniques to discover
which bands would be the most useful for a specific
classification task. We describe the design of a
prototype system and discuss its efficacy on a novel
data set from an imaging system that uses an
acoustically tuned optical filter. The data
preprocessing, training data extraction, training data
formatter, GP implementation, and classification image
generation tasks are detailed.",
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notes = "A joint meeting of the ninth International Conference
on Genetic Algorithms (ICGA-2000) and the fifth Annual
Genetic Programming Conference (GP-2000) Part of
\cite{whitley:2000:GECCO}",
- }
Genetic Programming entries for
Patrick J Rauss
Jason M Daida
Shahbaz A Chaudhary
Citations