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Exploiting Existing Modern Transcripts for Historical Handwritten Text Recognition

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Villegas, M.; Toselli, AH.; Romero Gómez, V.; Vidal, E. (2016). Exploiting Existing Modern Transcripts for Historical Handwritten Text Recognition. IEEE. https://doi.org/10.1109/ICFHR.2016.22

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/87627

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Title: Exploiting Existing Modern Transcripts for Historical Handwritten Text Recognition
Author: Villegas, Mauricio Toselli, Alejandro Héctor Romero Gómez, Verónica Vidal, Enrique
UPV Unit: Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat
Issued date:
Abstract:
[EN] Existing transcripts for historic manuscripts are a very valuable resource for training models useful for automatic recognition, aided transcription, and/or indexing of the remaining untranscribed parts of these ...[+]
Subjects: Handwritten Text Recognition , Historical Manuscripts , Modernized Transcripts , Transcript-image Alignment , Diplomatization
Copyrigths: Reserva de todos los derechos
ISBN: 978-1-5090-0981-7
Source:
(issn: 2167-6445 )
DOI: 10.1109/ICFHR.2016.22
Publisher:
IEEE
Publisher version: https://doi.org/10.1109/ICFHR.2016.0025
Conference name: 15th International Conference on Frontiers in Handwriting Recognition (ICFHR 2016)
Conference place: Shenzhen, China
Conference date: October, 23-26, 2016
Project ID: info:eu-repo/grantAgreement/EC/H2020/674943/EU
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.
Thanks:
We are very grateful to Carlos Lechner and Celio Hernández who helped in the creation of the ground truth of the Alcaraz dataset. This work has been partially supported by the European Union (EU) Horizon 2020 grant READ ...[+]
Type: Comunicación en congreso

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