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A New Classification Algorithm Based on Multi-kernel Support Vector Machine on Infrared Cloud Background Image

机译:基于多核支持向量机的红外云背景图像分类新算法

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A new classification algorithm based on multi-kernel support vector machine (SVM) was proposed for classification problems on infrared cloud background image. The experimental results show that the method integrates the advantages of polynomial kernel functions, Gaussian radial kernel functions and multilayer perception kernel functions. Compared with the traditional single-kernel SVM classification method, the proposed method has better performance both in local interpolation and global extrapolation, and is more suitable for SVM classification problems when the training sample size is small. Experimental results show the superiority of the proposed algorithm..
机译:针对红外云背景图像的分类问题,提出了一种基于多核支持向量机的分类算法。实验结果表明,该方法综合了多项式核函数,高斯径向核函数和多层感知核函数的优点。与传统的单核支持向量机分类方法相比,该方法在局部插值和全局外推上均具有更好的性能,并且在训练样本量较小的情况下更适合于支持向量机分类问题。实验结果证明了该算法的优越性。

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