Ensemble Image Classification Method Based on Genetic Image Network
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- @InProceedings{Nakayama:2010:EuroGP,
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author = "Shiro Nakayama and Shinichi Shirakawa and
Noriko Yata and Tomoharu Nagao",
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title = "Ensemble Image Classification Method Based on Genetic
Image Network",
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booktitle = "Proceedings of the 13th European Conference on Genetic
Programming, EuroGP 2010",
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year = "2010",
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editor = "Anna Isabel Esparcia-Alcazar and Aniko Ekart and
Sara Silva and Stephen Dignum and A. Sima Uyar",
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volume = "6021",
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series = "LNCS",
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pages = "313--324",
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address = "Istanbul",
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month = "7-9 " # apr,
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organisation = "EvoStar",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-642-12147-0",
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DOI = "doi:10.1007/978-3-642-12148-7_27",
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abstract = "Automatic image classification methods have been
required. Genetic Image Network for Image
Classification (GIN-IC) is one of the methods that
construct image classification algorithms
automatically, and its effectiveness has already been
proven. In our study, we try to improve the performance
of GIN-IC with AdaBoost algorithm using GIN-IC as weak
classifiers to complement with each other. We apply our
proposed method to three types of image classification
problems, and show the results in this paper. In our
method, discrimination rates for training images and
test images improved in the experiments compared with
the previous method GIN-IC.",
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notes = "Hill climbing. (1+4)-ES, mutation only Part of
\cite{Esparcia-Alcazar:2010:GP} EuroGP'2010 held in
conjunction with EvoCOP2010 EvoBIO2010 and
EvoApplications2010",
- }
Genetic Programming entries for
Shiro Nakayama
Shinichi Shirakawa
Noriko Yata
Tomoharu Nagao
Citations