Genetic programming for edge detection using multivariate density
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Fu:2013:GECCO,
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author = "Wenlong Fu and Mark Johnston and Mengjie Zhang",
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title = "Genetic programming for edge detection using
multivariate density",
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booktitle = "GECCO '13: Proceeding of the fifteenth annual
conference on Genetic and evolutionary computation
conference",
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year = "2013",
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editor = "Christian Blum and Enrique Alba and Anne Auger and
Jaume Bacardit and Josh Bongard and Juergen Branke and
Nicolas Bredeche and Dimo Brockhoff and
Francisco Chicano and Alan Dorin and Rene Doursat and
Aniko Ekart and Tobias Friedrich and Mario Giacobini and
Mark Harman and Hitoshi Iba and Christian Igel and
Thomas Jansen and Tim Kovacs and Taras Kowaliw and
Manuel Lopez-Ibanez and Jose A. Lozano and Gabriel Luque and
John McCall and Alberto Moraglio and
Alison Motsinger-Reif and Frank Neumann and Gabriela Ochoa and
Gustavo Olague and Yew-Soon Ong and
Michael E. Palmer and Gisele Lobo Pappa and
Konstantinos E. Parsopoulos and Thomas Schmickl and Stephen L. Smith and
Christine Solnon and Thomas Stuetzle and El-Ghazali Talbi and
Daniel Tauritz and Leonardo Vanneschi",
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isbn13 = "978-1-4503-1963-8",
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pages = "917--924",
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keywords = "genetic algorithms, genetic programming",
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month = "6-10 " # jul,
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organisation = "SIGEVO",
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address = "Amsterdam, The Netherlands",
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DOI = "doi:10.1145/2463372.2463485",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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abstract = "The combination of local features in edge detection
can generally improve detection performance. However,
how to effectively combine different basic features
remains an open issue and needs to be investigated.
Multivariate density is a generalisation of the
one-dimensional (univariate) distribution to higher
dimensions. In order to effectively construct composite
features with multivariate density, a Genetic
Programming (GP) system is proposed to evolve
Bayesian-based programs. An evolved Bayesian-based
program estimates the relevant multivariate density to
construct a composite feature. The results of the
experiments show that the GP system constructs
high-level combined features which substantially
improve the detection performance.",
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notes = "Also known as \cite{2463485} GECCO-2013 A joint
meeting of the twenty second international conference
on genetic algorithms (ICGA-2013) and the eighteenth
annual genetic programming conference (GP-2013)",
- }
Genetic Programming entries for
Wenlong Fu
Mark Johnston
Mengjie Zhang
Citations