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Seafloor classification using acoustic backscatter echo-waveform - Artificial neural network applications

DRS at CSIR-National Institute of Oceanography

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Title Seafloor classification using acoustic backscatter echo-waveform - Artificial neural network applications
 
Creator Chakraborty, B.
Mahale, V.
Navelkar, G.S.
Desai, R.G.P.
 
Subject echosoundind
acoustic equipment
echosounders
backscatter
continental margins
ocean floor
sediments
performance assessment
 
Description In this paper seafloor classifications system based on artificial neural network (ANN) has been designed. The ANN architecture employed here is a combination of Self Organizing Feature Map (SOFM) and Linear Vector Quantization (LVQ1). Currently acquired echo-waveform data acquired using single beam echo-sounder from twelve seafloor sediment locations from central part of the western continental shelf of India is analyzed and performance of the classifier is presented in this paper.
 
Date 2008-02-12T04:38:06Z
2008-02-12T04:38:06Z
2006
 
Type Conference Article
 
Identifier Oceans`06 IEEE Asia Pacific, 16-19 May 2006, Singapore, 4 pp.
http://drs.nio.org/drs/handle/2264/843
 
Language en
 
Rights Copyright [2006]. It is tried to respect the rights of the copyright holders to the best of the knowledge. If it is brought to our notice by copyright holder that the rights are voilated then the item would be withdrawn.
 
Publisher IEEE Singapore Section Secretariat