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文件名称:Unsupervised_Learning_of_Human_Action_Categories.r
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- 上传时间:2012-11-16
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基于时空域稀疏性表征的人的行为识别和理解的算法研究的论文,采用了非监督学习的方法,具有很*价值。-When the airspace based on sparse representation of human behavior recognition and understanding of the algorithm research paper, using non-supervised learning method, has great reference value.
相关搜索: 行为识别
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Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words.pdf
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