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

http://link.springer.com/chapter/10.1007%2F978-3-642-32937-1_17

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"
}