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Generation of Hypergraphs from the N-Best Parsing of 2D-Probabilistic Context-Free Grammars for Mathematical Expression Recognition

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Generation of Hypergraphs from the N-Best Parsing of 2D-Probabilistic Context-Free Grammars for Mathematical Expression Recognition

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dc.contributor.author Noya, Ernesto es_ES
dc.contributor.author Sánchez Peiró, Joan Andreu es_ES
dc.contributor.author Benedí Ruiz, José Miguel es_ES
dc.date.accessioned 2023-12-19T09:22:46Z
dc.date.available 2023-12-19T09:22:46Z
dc.date.issued 2021-01-15 es_ES
dc.identifier.isbn 978-1-7281-8808-9 es_ES
dc.identifier.uri http://hdl.handle.net/10251/200908
dc.description.abstract [EN] We consider hypergraphs as a tool obtained with bidimensional Probabilistic Context-Free Grammars to compactly represent the result of the n-best parse trees for an input image that represents a mathematical expression. More specifically, in this paper we propose: i) an algorithm to compute the N-best parse trees from a 2D-PCFGs, ii) an algorithm to represent the n-best parse trees using a compact representation in the form of hypergraphs, and iii) a formal framework for the development of inference algorithms (inside and outside) and normalization strategies of hypergraphs. es_ES
dc.description.sponsorship This work has been partially supported by the Ministerio de Ciencia y Tecnolog ' ia under the grant TIN2017-91452-EXP (IBEM) and by the Generalitat Valenciana under the grant PROMETEO/2019/121 (DeepPattern). es_ES
dc.language Inglés es_ES
dc.publisher IEEE es_ES
dc.relation.ispartof 2020 25th International Conference on Pattern Recognition (ICPR) es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Mathematical expression recognition es_ES
dc.subject Probabilistic Context-Free Grammars es_ES
dc.subject N-best parse trees es_ES
dc.subject Hypergraphs. es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Generation of Hypergraphs from the N-Best Parsing of 2D-Probabilistic Context-Free Grammars for Mathematical Expression Recognition es_ES
dc.type Comunicación en congreso es_ES
dc.type Capítulo de libro es_ES
dc.identifier.doi 10.1109/ICPR48806.2021.9412273 es_ES
dc.relation.projectID info:eu-repo/grantAgreement///PROMETEO%2F2019%2F121//DEEP LEARNING FOR ADAPTATIVE AND MULTIMODAL INTERACTION IN PATTERN RECOGNITION/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//TIN2017-91452-EXP//INDEXACION Y BUSQUEDA DE EXPRESIONES MATEMATICAS A GRAN ESCALA EN CORPUS MASIVOS DE DOCUMENTOS IMPRESOS/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica es_ES
dc.description.bibliographicCitation Noya, E.; Sánchez Peiró, JA.; Benedí Ruiz, JM. (2021). Generation of Hypergraphs from the N-Best Parsing of 2D-Probabilistic Context-Free Grammars for Mathematical Expression Recognition. IEEE. 5696-5703. https://doi.org/10.1109/ICPR48806.2021.9412273 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename 25th International Conference on Pattern Recognition (ICPR 2020) es_ES
dc.relation.conferencedate Enero 10-15,2021 es_ES
dc.relation.conferenceplace Online es_ES
dc.relation.publisherversion https://doi.org/10.1109/ICPR48806.2021.9412273 es_ES
dc.description.upvformatpinicio 5696 es_ES
dc.description.upvformatpfin 5703 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.pasarela S\450427 es_ES


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