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STEM-END/CALYX DETECTION IN APPLE FRUITS Comparison of Feature Selection Methods and Classifiers

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Part of the book series: Computational Imaging and Vision ((CIVI,volume 32))

Abstract

A multiple classifier system to localize stem-ends and calyxes of apple fruits was introduced previously. In this paper we not only introduce a new decision step to this system, but also provide comparisons of several feature selection algorithms and classifiers used. Our results prove that floating forward selection is the best within heuristic methods and support vector machines are better than nearest neighbor classifier in discriminating stem-ends/calyxes from defects.

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© 2006 Springer

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Unay, D., Gosselin, B. (2006). STEM-END/CALYX DETECTION IN APPLE FRUITS Comparison of Feature Selection Methods and Classifiers. In: Wojciechowski, K., Smolka, B., Palus, H., Kozera, R., Skarbek, W., Noakes, L. (eds) Computer Vision and Graphics. Computational Imaging and Vision, vol 32. Springer, Dordrecht. https://doi.org/10.1007/1-4020-4179-9_61

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  • DOI: https://doi.org/10.1007/1-4020-4179-9_61

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-4178-5

  • Online ISBN: 978-1-4020-4179-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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