Classification of Spectral Imagery Using Genetic Programming

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

@InProceedings{Rauss:2000:GECCO,

• author = "Patrick J. Rauss and Jason M. Daida and Shahbaz Chaudhary",
• title = "Classification of Spectral Imagery Using Genetic Programming",
• pages = "726--733",
• year = "2000",
• publisher = "Morgan Kaufmann",
• booktitle = "Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2000)",
• editor = "Darrell Whitley and David Goldberg and Erick Cantu-Paz and Lee Spector and Ian Parmee and Hans-Georg Beyer",
• address = "Las Vegas, Nevada, USA",
• publisher_address = "San Francisco, CA 94104, USA",
• month = "10-12 " # jul,
• keywords = "genetic algorithms, genetic programming",
• ISBN = "1-55860-708-0",
• URL = "http://gpbib.cs.ucl.ac.uk/gecco2000/RW157.pdf",
• size = "8 pages",
• abstract = "This paper describes an initial use of genetic programming as a discovery engine that derives two sets of information from hyper-spectral imagery. The first consists of a set of classification algorithms learned from the data. The second consists of reduced subsets of the most germane bands for use in a given classification, since not all spectral bands are of use in deriving a particular classification algorithm. Currently, there are only a few techniques to discover which bands would be the most useful for a specific classification task. We describe the design of a prototype system and discuss its efficacy on a novel data set from an imaging system that uses an acoustically tuned optical filter. The data preprocessing, training data extraction, training data formatter, GP implementation, and classification image generation tasks are detailed.",
• notes = "A joint meeting of the ninth International Conference on Genetic Algorithms (ICGA-2000) and the fifth Annual Genetic Programming Conference (GP-2000) Part of \cite{whitley:2000:GECCO}",

}

Genetic Programming entries for Patrick J Rauss Jason M Daida Shahbaz A Chaudhary

Citations