Comparison Study of Controlling Bloat Model of GP in Constructing Filter for Cell Image Segmentation Problems
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Yamaguchi:2012:CEC,
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title = "Comparison Study of Controlling Bloat Model of {GP} in
Constructing Filter for Cell Image Segmentation
Problems",
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author = "Hiroaki Yamaguchi and Tomoyuki Hiroyasu and
Sakito Nunokawa and Noriko Koizumi and Naoki Okumura and
Hisatake Yokouchi and Mitsunori Miki and
Masato Yoshimi",
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pages = "3503--3510",
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booktitle = "Proceedings of the 2012 IEEE Congress on Evolutionary
Computation",
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year = "2012",
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editor = "Xiaodong Li",
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month = "10-15 " # jun,
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DOI = "doi:10.1109/CEC.2012.6252995",
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address = "Brisbane, Australia",
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ISBN = "0-7803-8515-2",
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keywords = "genetic algorithms, genetic programming, Applications
of Evolutionary Computation in Biomedical Engineering
(IEEE-CEC), Biometrics, bioinformatics and biomedical
applications",
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abstract = "The final goal of this research is to construct a cell
image analysis system for supporting corneal
regenerative medicine. Existing image analysis software
requires knowledge about image processing of users
because users have to combine several image processing
on its analysis. Therefore, several types of methods to
construct the objective image processing automatically
using genetic programming (GP) have been proposed.
However, in conventional researches, only canonical GP
models were used. In this paper, GP models suited to
cell image segmentation are investigated applying
proposed controlling bloat model of GP. Applied models
were six types in addition to the canonical model;
those are Double Tournament, Tarpeian, Non-Destructive
Crossover (NDC), Recombinative Hill-Climbing (RHC),
Spatial Structure + Elitism (SS+E). The combination of
image processing obtained by these GP models and the
robustness are examined by comparative experiments,
using corned endothelium cell image. The experiment
results showed that SS+E is superior to other models in
both robustness and image processing constructed for
cell image segmentation, without depending on
parameters of tree depth limit and penalty.",
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notes = "WCCI 2012. CEC 2012 - A joint meeting of the IEEE, the
EPS and the IET.",
- }
Genetic Programming entries for
Hiroaki Yamaguchi
Tomoyuki Hiroyasu
Sakito Nunokawa
Noriko Koizumi
Naoki Okumura
Hisatake Yokouchi
Mitsunori Miki
Masato Yoshimi
Citations