DocumentCode
2288754
Title
Seafloor Classification Using Acoustic Backscatter Echo-waveform - Artificial Neural Network Applications
Author
Chakraborty, Bishwajit ; Mahale, Vasudev ; Navelkar, Gajanan ; Desai, R. G Prabhu
Author_Institution
Nat. Inst. of Oceanogr., Dona Paula
fYear
2007
fDate
16-19 May 2007
Firstpage
1
Lastpage
4
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.
Keywords
oceanographic techniques; sediments; self-organising feature maps; underwater sound; vector quantisation; acoustic backscatter echo waveform; artificial neural network; linear vector quantization; seafloor classification; seafloor sediment locations; self organizing feature map; Acoustic applications; Artificial neural networks; Backscatter; Data acquisition; Frequency; Grain size; Organizing; Sampling methods; Sea floor; Sediments;
fLanguage
English
Publisher
ieee
Conference_Titel
OCEANS 2006 - Asia Pacific
Conference_Location
Singapore
Print_ISBN
978-1-4244-0138-3
Electronic_ISBN
978-1-4244-0138-3
Type
conf
DOI
10.1109/OCEANSAP.2006.4393981
Filename
4393981
Link To Document