The Use of Genetic Programming for Learning 3D Craniofacial Shape Quantifications

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Atmosukarto:2010:UGP:1904935.1906046,

• author = "Indriyati Atmosukarto and Linda G. Shapiro and Carrie Heike",
• title = "The Use of Genetic Programming for Learning {3D} Craniofacial Shape Quantifications",
• booktitle = "Proceedings of the 2010 20th International Conference on Pattern Recognition",
• year = "2010",
• editor = "Aytul Ercil",
• pages = "2444--2447",
• address = "Istanbul, Turkey",
• month = "23-26 " # aug,
• organisation = "International Association for Pattern Recognition (IAPR)",
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, 3D Shape quantification",
• isbn13 = "978-0-7695-4109-9",
• URL = "http://www.cs.washington.edu/research/VACE/Multimedia/icpr10_Atmosukarto.pdf",
• URL = "http://grail.cs.washington.edu/pub/papers/atmosukarto2010uog.pdf",
• DOI = "doi:10.1109/ICPR.2010.598",
• acmid = "1906046",
• size = "4 pages",
• abstract = "Craniofacial disorders commonly result in various head shape dysmorphologies. The goal of this work is to quantify the various 3D shape variations that manifest in the different facial abnormalities in individuals with a craniofacial disorder called 22q11.2 Deletion Syndrome. Genetic programming (GP) is used to learn the different 3D shape quantifications. Experimental results show that the GP method achieves a higher classification rate than those of human experts and existing computer algorithms [1], [2].",
• notes = "ICPR '10",

}

Genetic Programming entries for Indriyati Atmosukarto Linda G Shapiro Carrie Heike

Citations