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Erschienen in:
2007 | OriginalPaper | Buchkapitel
A Genetic Programming Classifier Design Approach for Cell Images
verfasst von : Aydın Akyol, Yusuf Yaslan, Osman Kaan Erol
Erschienen in: Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Verlag: Springer Berlin Heidelberg
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This paper describes an approach for the use of genetic programming (GP) in classification problems and it is evaluated on the automatic classification problem of pollen cell images. In this work, a new reproduction scheme and a new fitness evaluation scheme are proposed as advanced techniques for GP classification applications. Also an effective set of pollen cell image features is defined for cell images. Experiments were performed on Bangor/Aberystwyth Pollen Image Database and the algorithm is evaluated on challenging test configurations. We reached at 96 % success rate on the average together with significant improvement in the speed of convergence.