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Learning the Structure of High-Dimensional Manifolds with Self-Organizing Maps for Accurate Information Extraction

机译：利用自组织映射学习高维流形的结构以准确提取信息

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This paper was submitted by the author prior to final official version. For official version please see http://hdl.handle.net/1911/70515

机译：本文是在最终正式版之前由作者提交的。有关正式版本，请访问http://hdl.handle.net/1911/70515

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作者
Zhang Lili;
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年度 2011
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原文格式 PDF
正文语种 eng
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4. Analyzing the Formation of Structure in High-Dimensional Self-Organizing Maps Reveals Differences to Feature Map Models [C] . Maximilian Riesenhuber, Hans-Ulrich bauer, Theo Geisel 1996 International Conference on Artificial Neural Networks - ICANN 96 Bochum, Germany, July 16-19, 1996 . 1996

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5. Learning the Structure of High-Dimensional Manifolds with Self-Organizing Maps for Accurate Information Extraction. [D] . Zhang, Lili. 2011

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6. Automatic Extraction of Appendix from Ultrasonography with Self-Organizing Map and Shape-Brightness Pattern Learning [O] . Kwang Baek Kim, Doo Heon Song, Hyun Jun Park 2006

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7. Learning the Structure of High-Dimensional Manifolds with Self-Organizing Maps for Accurate Information Extraction [O] . Zhang Lili 2011

机译：利用自组织映射学习高维流形的结构以准确提取信息

Learning the Structure of High-Dimensional Manifolds with Self-Organizing Maps for Accurate Information Extraction

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