| 一种用于海底类型聚类的新方法(英文) |
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| 作者单位： | School of Geodesy and Geomatics，Wuhan University |
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| 基金项目： | Supported by the National 863 High-Tech Program of China （No. 2007AA12Z326）. |
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| 摘 要： | By using sonar imaging, this paper presents a new algorithm for the clustering of seabed types based on the self-organizing feature maps （SOFM） neural network. The theory as well as data processing is studied in detail. Some valuable conclusions and suggestions are given
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| 关 键 词： | 海底类型聚类 海洋测量学 SOFM 测量方法 |
| 收稿时间： | 23 March 2006 |
A new algorithm for clustering of seabed types |
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| Authors: | Jianhu Zhao Hongmei Zhang Feihu Ma Juanjuan Li |
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| Institution: | (1) School of Geodesy and Geomatics, Wuhan University, 129 Luoyu Road, Wuhan, 430079, China |
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| Abstract: | By using sonar imaging, this paper presents a new algorithm for the clustering of seabed types based on the self-organizing feature maps (SOFM) neural network. The theory as well as data processing is studied in detail. Some valuable conclusions and suggestions are given. |
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| Keywords: | sonar image self-organizing feature maps (SOFM) clustering of seabed types |
| 本文献已被 CNKI 维普 SpringerLink 等数据库收录！ |
