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dc.contributor.authorMenezes, A.A.A.
dc.contributor.authorNaik, M.
dc.contributor.authorFernandes, W.A.
dc.contributor.authorHaris, K.
dc.contributor.authorChakraborty, B.
dc.contributor.authorEstiberio, S.
dc.contributor.authorLohani, R.B.
dc.date.accessioned2015-07-10T10:52:58Z
dc.date.available2015-07-10T10:52:58Z
dc.date.issued2015
dc.identifier.citationProceedings of the International Symposium on Underwater Technology (UT-2015), 23-25 February 2015. ; National Institute of Ocean Technology, Chennai; India; 2015; UT15-121
dc.identifier.urihttp://drs.nio.org/drs/handle/2264/4729
dc.description.abstractIn this work, we have developed a classification technique to characterize the seafloor of the Gaveshani (coralline) bank area using multi-beam backscatter data. Softcomputational techniques like the artificial neural networks (ANNs) based unsupervised self-organizing maps (SOM) architecture is used to determine the existence of six classes. Thereafter, 55 segments were identified for data segmentation, employing six profiles selected from the backscatter maps, using the fuzzy c-means (FCM) algorithms. The gridded map of the segmented seafloor backscatter data was overlaid on the coregistered backscatter map to understand the distribution of the overlying sediment material on the bank
dc.language.isoen
dc.publisherNIOT, Chennai
dc.rightsCopyright [2015]. All efforts have been made to respect the copyright to the best of our knowledge. Inadvertent omissions, if brought to our notice, stand for correction and withdrawal of document from this repository.
dc.subjectOCEANOGRAPHY AND LIMNOLOGY
dc.titleFine scale analyses of a coralline bank mapped using multi-beam backscatter data
dc.typeConference Article


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