Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/2626
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dc.contributor.authorAbbas, Abdulwaheden_US
dc.contributor.authorNasri, Ahmad Hen_US
dc.date.accessioned2020-12-23T09:17:00Z-
dc.date.available2020-12-23T09:17:00Z-
dc.date.issued2017-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/2626-
dc.description.abstractAs originally conceived, T-splines generalize both NURBS and Subdivision surfaces. Central to T-splines is the knot refinement algorithm, which seems to successfully import the local characteristic of B-spline and NURBS curve knot insertion. However, the mathematical decisiveness manifested in curve knot insertion is nowhere to be seen in previously published versions of T-spline local refinement. In this respect, this paper gives a tutorial exposition of T-spline local refinement, interpreted in the spirit of a belief-revision metaphor. It also provides a detailed implementation of that, designed following the architecture of rule-based systems. Both of these are classical topics in traditional Artificial Intelligence Research.en_US
dc.language.isoengen_US
dc.subjectT-spline surfacesen_US
dc.subjectLocal refinementen_US
dc.subjectBelief revisionen_US
dc.subjectRule-based systemsen_US
dc.titleT-spline local refinement as a belief revision system: a rule-based implementationen_US
dc.typeJournal Articleen_US
dc.identifier.doi10.1080/16864360.2016.1273579-
dc.contributor.affiliationDepartment of Computer Scienceen_US
dc.description.volume14en_US
dc.description.issue5en_US
dc.description.startpage622en_US
dc.description.endpage631en_US
dc.date.catalogued2018-01-10-
dc.description.statusPublisheden_US
dc.identifier.ezproxyURLhttp://ezsecureaccess.balamand.edu.lb/login?url=https://doi.org/10.1080/16864360.2016.1273579en_US
dc.identifier.OlibID175950-
dc.relation.ispartoftextJournal of computer-aided design and applicationsen_US
dc.provenance.recordsourceOliben_US
Appears in Collections:Department of Computer Science
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