计算机科学 ›› 2008, Vol. 35 ›› Issue (12): 220-223.

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基于半监督流形学习的人脸识别方法

  

  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    重庆市自然基金资助项目(NQCSTC2006BB215).

  • Online:2018-11-16 Published:2018-11-16

摘要: 如何有效地将流形学习(Manifold learning,ML)和半监督学习(Semi-supervised learning,SSL)方法进行结合是近年来模式识别和机器学习领域研究的热点问题。提出一种基于半监督流形学习(Semi-supervised manifold learning,SSML)的人脸识别方法,它在部分有标签信息的人脸数据的情况下,通过利用人脸数据本身的非线性流形结构信息和部分标签信息来调整点与点之间的距离形成距离矩阵,而后基于被调整的距离矩阵进行线性近邻重建来实现维数约简,提取低维鉴

关键词: 流形学习 半监督学习 局部线性嵌入 维数约简 人脸识别

Abstract: Recently,manifold learning and semi-supervised learning are two hot topics in the field of machine learning. However, there are only a few researches on how to incorporate semi-supervised learning and manifold learning, especially for face recognition. A

Key words: Manifold learning, Semi-supervised learning, Local linear embedding (LLE), Dimensionality reduction, Face recognition

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