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《Geomatics and Information Science of Wuhan University》 2006-03
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Seafloor Classification from Multibeam Backscatter Data Using Learning Vector Quantization Neural Network

TANG Qiuhua~(1,2,3) ZHOU Xinghua~(2,3) DING Jisheng~(2) LIU Baohua~(2)(1 College of Marine Geosciences,Ocean University of China,5 Yushan Road,Qingdao 266003,China)(2 First Institute of Oceanography,State Oceanic Administration,6 Xianxialing Road,Qingdao 266061,China)(3 Department of Land Surveying and Geo-Informatics,The Hong Kong Polytechnic University,Hung Hom,Kowloon,Hong Kong)  
We utilize the seafloor backscatter strength data of each beam from multibeam sonar systems and the automatic classification technology to get the seafloor type identification maps.We primarily study on the seafloor classification using learning vector quantization(LVQ) neural network method.Using this classification method,we can rapidly identify all kinds of seafloor types,such as sand,gravel and rock in the experimental surveying areas.
【Fund】: 国家863计划资助项目(2004AA6160802001AA613040);; 国家海洋局青年海洋科学基金资助项目(2002306);; 香港理工大学资助项目(G-V931);; 香港RGC资助项目(B-Q734)
【CateGory Index】: P229.2
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