一种用于海底类型聚类的新方法(英文)

• 作 者: 赵建虎 张红梅 马飞虎 李娟娟
• 机 构: School of Geodesy and Geomatics, Wuhan University,
• 出 处: Geo-Spatial Information Science
• 发表日期: 2008年04期
• 关键词: clustering sonar SOFM organizing conclusions fulfill neighborhood texture 海底 top

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.

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. .