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Please use this identifier to cite or link to this item: http://drs.nio.org/drs/handle/2264/843

Title: Seafloor classification using acoustic backscatter echo-waveform - Artificial neural network applications
Authors: Chakraborty, B.
Mahale, V.
Navelkar, G.S.
Desai, R.G.P.
Citation: Oceans`06 IEEE Asia Pacific, 16-19 May 2006, Singapore, 4 pp.
Issue Date: 2006
Publisher: IEEE Singapore Section Secretariat
Abstract: 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.
Document type: Conference Article
Copyright: 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 If it is brought to our notice by copyright holder that the rights are voilated then the item would be withdrawn.
URI: http://drs.nio.org/drs/handle/2264/843
Appears in Collections:Geology & Geophysical Sciences

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