Amir Salimi
Faculty of Mining, Petroleum and Geophysics, Shahrood University of Technology, Shahrood, Iran
[ 1 ] - High performance of the support vector machine in classifying hyperspectral data using a limited dataset
To prospect mineral deposits at regional scale, recognition and classification of hydrothermal alteration zones using remote sensing data is a popular strategy. Due to the large number of spectral bands, classification of the hyperspectral data may be negatively affected by the Hughes phenomenon. A practical way to handle the Hughes problem is preparing a lot of training samples until the size ...
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