提出了一种基于支持向量机的改进的降维方法。

In this paper we present an improved dimensionality reduction method based on support vector machines.

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提出了一种基于层次型支持向量机的正面直立人脸检测方法，在这两方面作了改进。

A face detection method based on a hierarchical support vector machines (SVM) presents improved methods for both of these problems.

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首先分析了支持向量机原理，随后引入一种改进的径向基核函数，在此基础上，提出了一种改进核函数的SVM模式分类方法。

The theory of SVM is studied at first, then an ameliorated RBF kernel function is presented, based on which an improved kernel function pattern classification method of SVM is put forward.

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