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Word graphs size impact on the performance of handwriting document applications

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Word graphs size impact on the performance of handwriting document applications

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dc.contributor.author Toselli ., Alejandro Héctor es_ES
dc.contributor.author Romero Gómez, Verónica es_ES
dc.contributor.author Vidal, Enrique es_ES
dc.date.accessioned 2018-05-18T07:31:06Z
dc.date.available 2018-05-18T07:31:06Z
dc.date.issued 2017 es_ES
dc.identifier.issn 0941-0643 es_ES
dc.identifier.uri http://hdl.handle.net/10251/102206
dc.description.abstract [EN] Two document processing applications are con- sidered: computer-assisted transcription of text images (CATTI) and Keyword Spotting (KWS), for transcribing and indexing handwritten documents, respectively. Instead of working directly on the handwriting images, both of them employ meta-data structures called word graphs (WG), which are obtained using segmentation-free hand- written text recognition technology based on N-gram lan- guage models and hidden Markov models. A WG contains most of the relevant information of the original text (line) image required by CATTI and KWS but, if it is too large, the computational cost of generating and using it can become unafordable. Conversely, if it is too small, relevant information may be lost, leading to a reduction of CATTI or KWS performance. We study the trade-off between WG size and performance in terms of effectiveness and effi- ciency of CATTI and KWS. Results show that small, computationally cheap WGs can be used without loosing the excellent CATTI and KWS performance achieved with huge WGs. es_ES
dc.description.sponsorship Work partially supported by the Generalitat Valenciana under the Prometeo/2009/014 Project Grant ALMAMATER, by the Spanish MECD as part of the Valorization and I+D+I Resources program of VLC/CAMPUS in the International Excellence Campus program, and through the EU projects: HIMANIS (JPICH programme, Spanish Grant Ref. PCIN-2015-068) and READ (Horizon-2020 programme, Grant Ref. 674943). en_EN
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Neural Computing and Applications es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Computer-assisted transcription of text images es_ES
dc.subject Keyword spotting for handwritten text es_ES
dc.subject Historical handwritten manuscripts es_ES
dc.subject Word graphs es_ES
dc.subject Evaluation performance es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Word graphs size impact on the performance of handwriting document applications es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s00521-016-2336-2 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/674943/EU/Recognition and Enrichment of Archival Documents/ en_EN
dc.relation.projectID info:eu-repo/grantAgreement/Generalitat Valenciana//PROMETEO09%2F2009%2F014/ES/Adaptive learning and multimodality in pattern recognition (Almapater)/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//PCIN-2015-068/ES/INDEXACION DE MANUSCRITOS HISTORICOS PARA BUSQUEDAS CONTROLADAS POR EL USUARIO/ es_ES
dc.rights.accessRights Abierto es_ES
dc.date.embargoEndDate 2018-09-01 es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Toselli ., AH.; Romero Gómez, V.; Vidal, E. (2017). Word graphs size impact on the performance of handwriting document applications. Neural Computing and Applications. 28(9):2477-2487. https://doi.org/10.1007/s00521-016-2336-2 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s00521-016-2336-2 es_ES
dc.description.upvformatpinicio 2477 es_ES
dc.description.upvformatpfin 2487 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 28 es_ES
dc.description.issue 9 es_ES
dc.relation.pasarela S\338506 es_ES
dc.contributor.funder Generalitat Valenciana es_ES
dc.contributor.funder European Commission es_ES
dc.contributor.funder Ministerio de Economía, Industria y Competitividad es_ES
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