Transformation of Redundant Representations of Linear Genetic Programming into Canonical Forms for Efficient Extraction of Image Features

Created by W.Langdon from gp-bibliography.bib Revision:1.8010

@InProceedings{Watchareeruetai:2008:cec,

• author = "Ukrit Watchareeruetai and Yoshinori Takeuchi and Tetsuya Matsumoto and Noboru Ohnishi",
• title = "Transformation of Redundant Representations of Linear Genetic Programming into Canonical Forms for Efficient Extraction of Image Features",
• booktitle = "2008 IEEE World Congress on Computational Intelligence",
• year = "2008",
• editor = "Jun Wang",
• pages = "1996--2003",
• address = "Hong Kong",
• month = "1-6 " # jun,
• organization = "IEEE Computational Intelligence Society",
• publisher = "IEEE Press",
• isbn13 = "978-1-4244-1823-7",
• file = "EC0478.pdf",
• DOI = "doi:10.1109/CEC.2008.4631062",
• abstract = "Recently, evolutionary computation (EC) has been adopted to search for effective feature extraction programs for given image recognition problems. For this approach, feature extraction programs are constructed from a set of primitive operations (POs), which are usually general image processing and pattern recognition operations. In this paper, we focus on an approach based on a variation of linear genetic programming (LGP). We describe the causes of redundancies in LGP based representation, and propose a transformation that converts the redundant LGP representation into a canonical form, in which all redundancies are removed. Based on this transformation, we present a way to reduce computation time, i.e., the evolutionary search that avoids executions of redundant individuals. Experimental results demonstrate a success in computation time reduction; around 7-62percent of total compuation time can be reduced. Also, we have experimented with an evolutionary search that prohibits existence of redundant individuals. When selection pressure is high enough, its search performance is better than that of conventional evolutionary search.",
• keywords = "genetic algorithms, genetic programming",
• notes = "WCCI 2008 - A joint meeting of the IEEE, the INNS, the EPS and the IET.",

}

Genetic Programming entries for Ukrit WatchAreeruetai Yoshinori Takeuchi Tetsuya Matsumoto Noboru Ohnishi

Citations