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The pattern recognition of remote sensing images is based on the different spectral characteristics of surface features to identify the features type, mainly including the supervised classification and unsupervised classification. In this paper, the TM remote sensing images are preprocessed firstly, and then land-covered features are classified using the maximum likelihood method, the minimum distance...
Traditional pattern recognition techniques can not handle the classification of large datasets with both efficiency and effectiveness. In this context, the Optimum-Path Forest (OPF) classifier was recently introduced, trying to achieve high recognition rates and low computational cost. Although OPF was much faster than Support Vector Machines for training, it was slightly slower for classification...
A framework of remote sensing images classification based on Artificial Immune Recognition System (AIRS) is present in this papers. The relation between key parameters and the classification results are analyzed. As shown in the experiment results, the new framework inherits robustness of AIRS relative to key parameter. Experimental results show that this framework is better than Maximum Likelihood...
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