Detail publikace

Comparison of CGP and Age-Layered CGP Performance in Image Operator Evolution

SLANÝ, K.

Originální název

Comparison of CGP and Age-Layered CGP Performance in Image Operator Evolution

Anglický název

Comparison of CGP and Age-Layered CGP Performance in Image Operator Evolution

Jazyk

en

Originální abstrakt

This paper analyses the efficiency of the Cartesian Genetic Programming (CGP) methodology in the image operator design problem at the functional level. The CGP algorithm is compared with an age layering enhancement of the CGP algorithm by the means of achieved best results and their computational effort. Experimental results show that the Age-Layered Population Structure (ALPS) algorithm combined together with CGP can perform better in the task of image operator design in comparison with a common CGP algorithm.

Anglický abstrakt

This paper analyses the efficiency of the Cartesian Genetic Programming (CGP) methodology in the image operator design problem at the functional level. The CGP algorithm is compared with an age layering enhancement of the CGP algorithm by the means of achieved best results and their computational effort. Experimental results show that the Age-Layered Population Structure (ALPS) algorithm combined together with CGP can perform better in the task of image operator design in comparison with a common CGP algorithm.

Dokumenty

BibTex


@inproceedings{BUT30904,
  author="Karel {Slaný}",
  title="Comparison of CGP and Age-Layered CGP Performance in Image Operator Evolution",
  annote="This paper analyses the efficiency of the Cartesian Genetic Programming (CGP)
methodology in the image operator design problem at the functional level. The CGP
algorithm is compared with an age layering enhancement of the CGP algorithm by
the means of achieved best results and their computational effort. Experimental
results show that the Age-Layered Population Structure (ALPS) algorithm combined
together with CGP can perform better in the task of image operator design in
comparison with a common CGP algorithm.",
  address="Springer Verlag",
  booktitle="Genetic Programming, 12th European Conference, EuroGP 2009",
  chapter="30904",
  edition="Lecture Notes in Computer Science",
  howpublished="print",
  institution="Springer Verlag",
  journal="Lecture Notes in Computer Science (IF 0,513)",
  year="2009",
  month="april",
  pages="351--361",
  publisher="Springer Verlag",
  type="conference paper"
}