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Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/50714
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dc.contributor.authorSirinnared Winaipanichen_US
dc.contributor.authorSansanee Auephanwiriyakulen_US
dc.contributor.authorNipon Theera-Umponen_US
dc.date.accessioned2018-09-04T04:44:38Z-
dc.date.available2018-09-04T04:44:38Z-
dc.date.issued2010-07-30en_US
dc.identifier.other2-s2.0-77954922581en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=77954922581&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/50714-
dc.description.abstractLaser line scanner are becoming very popular very recently because there is no touching the surface to determine coordinates. However, there are some missing points because of some parts of objects are out of sight from the laser. Therefore, in this research we introduce an automatic method to estimate missing points in a Cartesian coordinate system using fuzzy support vector regression (FSVR). We also compare our result with the one from support vector regression (SVR). The results show that the FSVR is a suitable method in missing 3D coordinates estimation.en_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.title3D missing point estimation using fuzzy support vector regressionen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleECTI-CON 2010 - The 2010 ECTI International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technologyen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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