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A Bayesian Nonparametric Approach to Clustering Data from Underwater Robotic Surveys Daniel M. Steinberg, Ariell Friedman, Oscar Pizarro and Stefan B. Williams Abstract The use of robots for scientific mapping and explo
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Document Date: 2011-08-18 11:40:14

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File Size: 3,39 MB

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City

Scott Reef / /

Company

Intel / /

Country

Australia / /

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Facility

University of Sydney / /

IndustryTerm

overall free energy / dot product / filter bank / unsupervised clustering algorithms / robotic applications / free energy / negative free energy / max free energy / style algorithms / /

Organization

Williams and Oscar Pizarro Australian Centre for Field Robotics / University of Sydney / /

Person

Ariell Friedman / B. Williams Abstract / Oscar Pizarro / Stefan B. Williams / Daniel M. Steinberg / /

Position

marine scientist / /

Product

Expectation-Maximisation / /

ProgrammingLanguage

C++ / /

ProvinceOrState

Western Australia / Tasmania / /

Region

Western Australia / /

Technology

Expectation-Maximisation style algorithms / 7 Algorithm / RAM / variational Bayes algorithm / unsupervised clustering algorithms / 2.2 The Variational Bayes algorithm / /

SocialTag