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一种鲁棒的监督流形学习算法及其在植物叶片分类中的应用

, PP. 836-841

Keywords: 流形学习,鲁棒性监督等度规映射(RS-Isomap),植物叶片分类,加权主分量分析(WPCA),支持向量机

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Abstract:

结合数据点的类别信息、局部信息和数据点的可信度,给出一种测地距离定义。在此基础上,提出一种改进的鲁棒性监督等度规映射算法,并应用于植物叶片分类中。首先利用改进的等度规映射将叶片图像投影到低维流形空间。然后采用支持向量机分类器进行植物叶片图像分类与识别。最后利用20种实际植物叶片图像进行植物叶片图像分类实验。实验结果表明该方法是有效可行的。

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