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Practical Evaluation of Efficient Fitness Functions for Binary Images

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3449))

Abstract

Genetic Programming can be used to evolve complex objects. One field, where GP may be used is image analysis. There are several works using evolutionary methods to process, analyze or classify images. All these procedures need an appropriate fitness function, that is a similarity measure. However, computing such measures usually needs a lot of computational time. To solve this problem, the notion of efficiently computable fitness functions was introduced, and their theory was already examined in detail. In contrast to that work, in this paper the practical aspects of these fitness functions are discussed.

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References

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© 2005 Springer-Verlag Berlin Heidelberg

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Ványi, R. (2005). Practical Evaluation of Efficient Fitness Functions for Binary Images. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2005. Lecture Notes in Computer Science, vol 3449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32003-6_32

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  • DOI: https://doi.org/10.1007/978-3-540-32003-6_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25396-9

  • Online ISBN: 978-3-540-32003-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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