The application of rough set and Kohonen network to feature selection for object extraction
Pan, Li, Zheng, Hong and Nahavandi, Saeid 2003, The application of rough set and Kohonen network to feature selection for object extraction, in 2003 International Conference on Machine Learning and Cybernetics,, IEEE Xplore, Piscataway, N.J., pp. 1185-1189.
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Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contexts including pattern recognition, images understanding and machine learning. The paper describes an application of rough sets method to feature selection and reduction in texture images recognition. The proposed methods include continuous data discretization based on Kohonen neural network and maximum covariance, and rough set algorithms for feature selection and reduction. The experiments on trees extraction from aerial images show that the methods presented in this paper are practical and effective.
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Field of Research
090999 Geomatic Engineering not elsewhere classified
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