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dc.contributor.authorCelik, M.en_US
dc.contributor.authorYanikoglu, B.en_US
dc.date.accessioned2016-02-08T12:15:39Z
dc.date.available2016-02-08T12:15:39Z
dc.date.issued2011en_US
dc.identifier.issn15205363
dc.identifier.urihttp://hdl.handle.net/11693/28259
dc.description.abstractWe present a probabilistic framework for the mathematical expression recognition problem. The developed system is flexible in that its grammar can be extended easily thanks to its graph grammar which eliminates the need for specifying rule precedence. It is also optimal in the sense that all possible interpretations of the expressions are expanded without making early commitments or hard decisions. In this paper, we give an overview of the whole system and describe in detail the graph grammar and the parsing process used in the system, along with some preliminary results on character, structure and expression recognition performances. © 2011 IEEE.en_US
dc.language.isoEnglishen_US
dc.source.titleProceedings of the International Conference on Document Analysis and Recognition, ICDARen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/ICDAR.2011.41en_US
dc.subject2D-grammaren_US
dc.subjectgraph grammaren_US
dc.subjecthandwriting recognitionen_US
dc.subjectmathematical equationen_US
dc.subjectOCRen_US
dc.subjectonlineen_US
dc.subject2D-grammaren_US
dc.subjectGraph grammaren_US
dc.subjectHandwriting recognitionen_US
dc.subjectMathematical equationsen_US
dc.subjectonlineen_US
dc.subjectContext sensitive grammarsen_US
dc.subjectGraph theoryen_US
dc.subjectOptical character recognitionen_US
dc.subjectFormal languagesen_US
dc.titleProbabilistic mathematical formula recognition using a 2D context-free graph grammaren_US
dc.typeConference Paperen_US
dc.departmentDepartment of Computer Engineering
dc.citation.spage161en_US
dc.citation.epage166en_US
dc.identifier.doi10.1109/ICDAR.2011.41en_US


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