Detail publikace
Acceleration of Evolutionary Image Filter Design Using Coevolution in Cartesian GP
DRAHOŠOVÁ, M. SEKANINA, L.
Originální název
Acceleration of Evolutionary Image Filter Design Using Coevolution in Cartesian GP
Typ
článek v časopise - ostatní, Jost
Jazyk
angličtina
Originální abstrakt
The aim of this paper is to accelerate the task of evolutionary image filter design using coevolution of candidate filters and training vectors subsets. Two coevolutionary methods are implemented and compared for this task in the framework of Cartesian Genetic Programming (CGP). Experimental results show that only 15-20 % of original test vectors are needed to find an image filter which provides the same quality of filtering as the best filter evolved using the standard CGP which utilizes the whole training set. Moreover, the median time of evolution was reduced 2.99 times in comparison with the standard CGP.
Klíčová slova
Cartesian genetic programming, coevolution, fitness modeling, image filter design.
Autoři
DRAHOŠOVÁ, M.; SEKANINA, L.
Rok RIV
2012
Vydáno
24. 7. 2012
Nakladatel
Springer Verlag
Místo
Berlin
ISBN
978-3-642-32936-4
Kniha
The 12th International Conference on Parallel Problem Solving from Nature
ISSN
0302-9743
Periodikum
Lecture Notes in Computer Science
Ročník
2012
Číslo
7491
Stát
Spolková republika Německo
Strany od
163
Strany do
172
Strany počet
10
URL
BibTex
@article{BUT96949,
author="Michaela {Drahošová} and Lukáš {Sekanina}",
title="Acceleration of Evolutionary Image Filter Design Using Coevolution in Cartesian GP",
journal="Lecture Notes in Computer Science",
year="2012",
volume="2012",
number="7491",
pages="163--172",
doi="10.1007/978-3-642-32937-1\{_}17",
issn="0302-9743",
url="http://link.springer.com/chapter/10.1007%2F978-3-642-32937-1_17"
}