Ensemble Image Classification Method Based on Genetic Image Network

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Nakayama:2010:EuroGP,

• author = "Shiro Nakayama and Shinichi Shirakawa and Noriko Yata and Tomoharu Nagao",
• title = "Ensemble Image Classification Method Based on Genetic Image Network",
• booktitle = "Proceedings of the 13th European Conference on Genetic Programming, EuroGP 2010",
• year = "2010",
• editor = "Anna Isabel Esparcia-Alcazar and Aniko Ekart and Sara Silva and Stephen Dignum and A. Sima Uyar",
• volume = "6021",
• series = "LNCS",
• pages = "313--324",
• address = "Istanbul",
• month = "7-9 " # apr,
• organisation = "EvoStar",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-642-12147-0",
• DOI = "doi:10.1007/978-3-642-12148-7_27",
• 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.",
• 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