@inproceedings{66ea764eda7b4f10965e0ca71418975e,
title = "A genetic programming classifier design approach for cell images",
abstract = "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.",
keywords = "Cell classification, Classifier design, Genetic programming, Pollen classification",
author = "Aydin Akyol and Yusuf Yaslan and Erol, \{Osman Kaan\}",
year = "2007",
doi = "10.1007/978-3-540-75256-1\_76",
language = "English",
isbn = "9783540752554",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "878--888",
booktitle = "Symbolic and Quantitative Approaches to Reasoning with Uncertainty - 9th European Conference, ECSQARU 2007, Proceedings",
address = "Germany",
note = "9th European Conference on Symbolic and Qualitative Approaches to Reasoning with Uncertainty, ECSQARU 2007 ; Conference date: 31-10-2007 Through 02-11-2007",
}