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Abstract
We present a component-based, trainable system for detecting
frontal and near-frontal views of faces in still gray
images. The system consists of a two-level hierarchy of Support
Vector Machine (SVM) classifiers. On the first level,
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统计机器学习的支持向量机SVM在图像分割中的应用学习报告。-Statistical machine learning support vector machine SVM image segmentation study report.
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Least squares support vector machine SVM toolbox self code and installation methods, useful, tried
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In machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis. Given a
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支持向量机学习中用到的用Matlab编写的工具箱,不错的源码-Support vector machine (SVM) is used in the study using Matlab toolbox, good source
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数据挖掘算法,support vector machine算法源代码,用于分类-Data mining algorithm, support vector machine algorithm source code, is used for classification
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用matlab编写的用语分类的支持向量机 不错的源码 很好-Using matlab language classification support vector machine (SVM) good source is very good
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