Searched for: subject:"Bayes%5C+methods"
(1 - 4 of 4)
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Feng, R. (author), Luthi, S.M. (author), Gisolf, A. (author), Angerer, Erika (author)
In this paper, geological prior information is incorporated in the classification of reservoir lithologies after the adoption of Markov random fields (MRFs). The prediction of hidden lithologies is based on measured observations, such as seismic inversion results, which are associated with the latent categorical variables, based on the...
journal article 2018
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Snellen, M. (author), Gaida, T.C. (author), Koop, L. (author), Alevizos, Evangelos (author), Simons, D.G. (author)
Obtaining an overview of the spatial and temporal distribution of seabed sediments is of high interest for multiple research disciplines. Multibeam echosounders allow for the mapping of seabed sediments with high area coverage. In this paper, the repeatability of acoustic classification derived from multibeam echosounder backscatter is addressed...
journal article 2018
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Snellen, M. (author), Eleftherakis, S. (author), Amiri-Simkooei, A. (author), Koomans, R.L. (author), Simons, D.G. (author)
This contribution presents sediment classification results derived from different sources of data collected at the Dordtse Kil river, the Netherlands. The first source is a multi-beam echo-sounder (MBES). The second source is measurements taken with a gamma-ray scintillation detector, i.e., the Multi-Element Detection System for Underwater...
journal article 2013
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Amiri-Simkooei, A. (author), Snellen, M. (author), Simons, D.G. (author)
A method has recently been developed that employs multi-beam echo-sounder backscatter data to both obtain the number of sediment classes and discriminate between them by applying the Bayes decision rule to multiple hypotheses [ Simons and Snellen, Appl. Acoust. 70, 1258–1268 (2009) ]. In deep water, the number of scatter pixels within the beam...
journal article 2009
Searched for: subject:"Bayes%5C+methods"
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