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遥感学报 2010
Coupling GA with SVM for feature selection in high-resolution remote sensing target recognition
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Abstract:
As one of the key techniques for high-resolution remote sensing target recognition, feature selection focused on how to find the critical features in the feature set to represent the target. Generally, the classical methods for feature selection were as follows, principal component analysis, empirical method, etc. When using these classical methods, recognition accuracy was not guaranteed. In this paper, a new method was proposed, the main idea of which was to couple GA (Genetic Algorithm) and SVM (Support Vector Machine) for feature selection, and using recognition results to guide the revolution direction of GA. Meanwhile, to reduce the risk of premature convergence of the traditional GA, some modification had been made. The experi-ment demonstrated the effectiveness of the proposed method.