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ICFHR2016 Competition on Handwritten Text Recognition on the READ Dataset

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ICFHR2016 Competition on Handwritten Text Recognition on the READ Dataset

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dc.contributor.author Sánchez Peiró, Joan Andreu es_ES
dc.contributor.author Romero Gómez, Verónica es_ES
dc.contributor.author Toselli, Alejandro Héctor es_ES
dc.contributor.author Vidal, Enrique es_ES
dc.date.accessioned 2017-09-20T10:17:00Z
dc.date.available 2017-09-20T10:17:00Z
dc.date.issued 2016
dc.identifier.issn 2167-6445
dc.identifier.uri http://hdl.handle.net/10251/87615
dc.description © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. es_ES
dc.description.abstract [EN] This paper describes the Handwritten Text Recognition (HTR) competition on the READ dataset that has been held in the context of the International Conference on Frontiers in Handwriting Recognition 2016. This competition aims to bring together researchers working on off-line HTR and provide them a suitable benchmark to compare their techniques on the task of transcribing typical historical handwritten documents. Two tracks with different conditions on the use of training data were proposed. Ten research groups registered in the competition but finally five submitted results. The handwritten images for this competition were drawn from the German document Ratsprotokolle collection composed of minutes of the council meetings held from 1470 to 1805, used in the READ project. The selected dataset is written by several hands and entails significant variabilities and difficulties. The five participants achieved good results with transcriptions word error rates ranging from 21% to 47% and character error rates rating from 5% to 19%. es_ES
dc.description.sponsorship This work has been partially supported through the European Union's H2020 grant READ (Recognition and Enrichment of Archival Documents) (Ref: 674943), and the MINECO/FEDER UE project TIN2015-70924-C2-1-R.
dc.format.extent 6 es_ES
dc.language Inglés es_ES
dc.publisher IEEE es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Handwritten Text Recognition es_ES
dc.subject Historical documents es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title ICFHR2016 Competition on Handwritten Text Recognition on the READ Dataset es_ES
dc.type Comunicación en congreso es_ES
dc.identifier.doi 10.1109/ICFHR.2016.0120
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2015-70924-C2-1-R/ES/CONTEXTO, MULTIMODALIDAD Y COLABORACION DEL USUARIO EN PROCESADO DE TEXTO MANUSCRITO/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/674943/EU/Recognition and Enrichment of Archival Documents/
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.description.bibliographicCitation Sánchez Peiró, JA.; Romero Gómez, V.; Toselli, AH.; Vidal, E. (2016). ICFHR2016 Competition on Handwritten Text Recognition on the READ Dataset. IEEE. https://doi.org/10.1109/ICFHR.2016.0120 es_ES
dc.description.accrualMethod S es_ES
dc.relation.conferencename 15th International Conference on Frontiers in Handwriting Recognition (ICFHR 2016) es_ES
dc.relation.conferencedate October, 23-26, 2016 es_ES
dc.relation.conferenceplace Shenzhen, China es_ES
dc.relation.publisherversion https://doi.org/10.1109/ICFHR.2016.0120 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.senia 320612 es_ES
dc.contributor.funder European Commission
dc.contributor.funder Ministerio de Economía y Competitividad


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