Evolution of Image Filters on Graphics Processor Units Using Cartesian Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8110
- @InProceedings{Harding:2008:cec,
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author = "Simon Harding",
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title = "Evolution of Image Filters on Graphics Processor Units
Using Cartesian Genetic Programming",
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booktitle = "2008 IEEE World Congress on Computational
Intelligence",
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year = "2008",
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editor = "Jun Wang",
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pages = "1921--1928",
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address = "Hong Kong",
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month = "1-6 " # jun,
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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isbn13 = "978-1-4244-1823-7",
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file = "EC0465.pdf",
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DOI = "doi:10.1109/CEC.2008.4631051",
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abstract = "Graphics processor units are fast, inexpensive
parallel computing devices. Recently there has been
great interest in harnessing this power for various
types of scientific computation, including genetic
programming. In previous work, we have shown that using
the graphics processor provides dramatic speed
improvements over a standard CPU in the context of
fitness evaluation. In this work, we use Cartesian
Genetic Programming to generate shader programs that
implement image filter operations. Using the GPU, we
can rapidly apply these programs to each pixel in an
image and evaluate the performance of a given filter.
We show that we can successfully evolve noise removal
filters that produce better image quality than a
standard median filter.",
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keywords = "genetic algorithms, genetic programming, Cartesian
Genetic Programming, GPU",
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notes = "WCCI 2008 - A joint meeting of the IEEE, the INNS, the
EPS and the IET.",
- }
Genetic Programming entries for
Simon Harding
Citations