Title | ||
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High-Resolution Image Classification Using the Dynamic Differential Evolutionary Algorithm Optimized Multi-scale Kernel Support Vector Machine Method. |
Abstract | ||
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With the fast development of remote sensing techniques, the spatial resolution of remote sensed image are improved significantly. However, the excessive spatial resolution leads to a sharp increase in data volume and spectral information confusion of objects. The multi-scale kernel learning (MSKL) method has shown an excellent advantage in classification of high-resolution satellite image. Nevertheless, the performance of the MSKL is dramatically influenced by the widths and weights of the Radial Basis Function (RBF) kernel, since its multi-scale kernel function is constructed by several RBF kernels. In order to achieve efficient multi-scale classifier, a new dynamic differential evolution (DE) algorithm is introduced in this paper. In addition, the spectral features and spatial fractal texture features of images are synthetically employed to construct the multi-scale kernel. The experimental results show that the multi-scale kernel based on the dynamic DE algorithm is superior to the traditional multi-scale kernel in obtaining a better multi-scale kernel classifier and with higher classification accuracy. |
Year | Venue | Field |
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2018 | BICS | Kernel (linear algebra),Radial basis function,Pattern recognition,Evolutionary algorithm,Computer science,Support vector machine,Differential evolution,Artificial intelligence,Contextual image classification,Image resolution,Kernel (statistics) |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
14 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Xueqian Rong | 1 | 0 | 1.01 |
Aizhu Zhang | 2 | 62 | 9.98 |
Genyun Sun | 3 | 149 | 17.27 |
hui huang | 4 | 84 | 17.04 |
Ping Ma | 5 | 33 | 4.85 |