作业帮这些文字怎么翻译成汉语.AbstractThis term paper outlines the basics of non-negative matrix factorization and is based on thework of Daniel D. Lee and H. Sebastian Seung [7], [8]. It has been composed within the scopeof the seminar Machine L
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![这些文字怎么翻译成汉语.AbstractThis term paper outlines the basics of non-negative matrix factorization and is based on thework of Daniel D. Lee and H. Sebastian Seung [7], [8]. It has been composed within the scopeof the seminar Machine L](/uploads/image/z/7433984-56-4.jpg?t=%E8%BF%99%E4%BA%9B%E6%96%87%E5%AD%97%E6%80%8E%E4%B9%88%E7%BF%BB%E8%AF%91%E6%88%90%E6%B1%89%E8%AF%AD.AbstractThis+term+paper+outlines+the+basics+of+non-negative+matrix+factorization+and+is+based+on+thework+of+Daniel+D.+Lee+and+H.+Sebastian+Seung+%5B7%5D%2C+%5B8%5D.+It+has+been+composed+within+the+scopeof+the+seminar+Machine+L)
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这些文字怎么翻译成汉语.AbstractThis term paper outlines the basics of non-negative matrix factorization and is based on thework of Daniel D. Lee and H. Sebastian Seung [7], [8]. It has been composed within the scopeof the seminar Machine L
这些文字怎么翻译成汉语.
Abstract
This term paper outlines the basics of non-negative matrix factorization and is based on the
work of Daniel D. Lee and H. Sebastian Seung [7], [8]. It has been composed within the scope
of the seminar Machine Learning in Computer Vision hold during the winter term ’06/’07
by Prof. Dr. J. Schmidhuber and Dipl.-Inf. C. Osendorfer at the Technische Universit¨at
M¨unchen. It describes fundamental concepts, provides an overview over similar methods
such as principal component analysis (PCA) and gives some practical examples for possible
applications in the field of computer vision.
Copyright
这些文字怎么翻译成汉语.AbstractThis term paper outlines the basics of non-negative matrix factorization and is based on thework of Daniel D. Lee and H. Sebastian Seung [7], [8]. It has been composed within the scopeof the seminar Machine L
这篇基于Daniel D.Lee and H.Sebastian Seung的论文主要介绍非负矩阵因子化.
这篇论文在’06/’07冬季学期由慕尼黑大学的 Dr.J.Schmidhuber and Dipl.-Inf.C.Osendorfer开展的计算机视觉中的机械学习研讨会中撰写完成.
本文描述了一些基本概念,提供了相似方法的概述,例如主成分分析法.并且为在计算机视觉中的可能的应用举了实用的例子.