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dc.contributorFacultad de Veterinariaes_ES
dc.contributor.authorBlanco Medina, Pablo
dc.contributor.authorFidalgo Fernández, Eduardo 
dc.contributor.authorAlegre Gutiérrez, Enrique 
dc.contributor.authorAl Nabki, Mohamed Wesam 
dc.contributor.authorChaves, Deisy
dc.contributor.editorCalvo Rolle, José Luis
dc.contributor.editorCasteleiro Roca, José Luis
dc.contributor.editorFernández Ibáñez, María Isabel
dc.contributor.editorFontenla Romero, Óscar
dc.contributor.editorJove Pérez, Esteban
dc.contributor.editorLeira Rejas, Alberto José
dc.contributor.editorLópez Vázquez, José Antonio
dc.contributor.editorLoureiro Vázquez, Vanesa
dc.contributor.editorMeizoso López, María Carmen
dc.contributor.editorPérez Castelo, Francisco Javier
dc.contributor.editorPiñón Pazos, Andrés José
dc.contributor.editorQuintián Pardo, Héctor
dc.contributor.editorRivas Rodríguez, Juan Manuel
dc.contributor.editorRodríguez Gómez, Benigno
dc.contributor.editorVega Vega, Rafael Alejandro
dc.contributor.otherAlgebraes_ES
dc.date2019
dc.date.accessioned2024-05-06T12:46:40Z
dc.date.available2024-05-06T12:46:40Z
dc.identifier.citationBlanco Medina, P., Fidalgo Fernández, E., Alegre Gutiérrez, E., Wesam Al Nabki, M., & Chaves Sánchez, D. (2019). Enhancing text recognition on Tor Darknet images. En J. L. Calvo Rolle, J.-L. Casteleiro-Roca, I. Fernández-Ibáñez, Ó. Fontenla Romero, E. Jove Pérez, A. J. Leira-Rejas, J. A. López Vázquez, V. Loureiro-Vázquez, M.-C. Meizoso-López, F. J. Pérez Castelo, A. J. Piñón Pazos, H. Quintián Pardo, J. M. Rivas Rodríguez, B. A. Rodríguez Gómez, & R. A. Vega-Vega (eds.), XL Jornadas de Automática: libro de actas. Ferrol, 4-6 de septiembre de 2019.es_ES
dc.identifier.isbn978-84-9749-716-9es_ES
dc.identifier.urihttps://hdl.handle.net/10612/20424
dc.description.abstract[EN] ext Spotting can be used as an approach to retrieve information found in images that cannot be obtained otherwise, by performing text detection rst and then recognizing the located text. Examples of images to apply this task on can be found in Tor network images, which contain information that may not be found in plain text. When comparing both stages, the latter performs worse due to the low resolution of the cropped areas among other problems. Focusing on the recognition part of the pipeline, we study the performance of ve recognition approaches, based on state-ofthe- art neural network models, standalone OCR, and OCR enhancements. We complement them using string-matching techniques with two lexicons and compare computational time on ve di erent datasets, including Tor network images. Our nal proposal achieved 39,70% precision of text recognition in a custom dataset of images taken from Tor domainses_ES
dc.languageenges_ES
dc.publisherUniversidade da Coruñaes_ES
dc.relation.ispartofXL Jornadas de Automática: libro de actas. Ferrol, 4-6 de septiembre de 2019es_ES
dc.rightsAtribución-NoComercial-CompartirIgual 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectInformáticaes_ES
dc.subject.otherText spottinges_ES
dc.subject.otherText recognitiones_ES
dc.subject.otherOCRes_ES
dc.subject.otherCybersecurityes_ES
dc.subject.otherTor darknetes_ES
dc.titleEnhancing text recognition on Tor Darknet imageses_ES
dc.typeinfo:eu-repo/semantics/conferenceProceedingses_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.page.initial828es_ES
dc.page.final835es_ES
dc.subject.unesco1207.03 Cibernéticaes_ES
dc.subject.unesco1203.17 Informáticaes_ES
dc.subject.unesco3304.05 Sistemas de Reconocimiento de Caractereses_ES
dc.description.projectThis research is supported by the framework agreement between Universidad de Le´on and INCIBE (Spanish National Cybersecurity Institute) under Addendum 01. We acknowledge NVIDIA Corporation with the donation of the Titan Xp GPU used for this research. This research has also been funded with support from the European Commission under the 4NSEEK project with Grant Agreement 821966. This publication reflects the views only of the author, and the European Commission cannot be held responsible for any use which may be made of the information contained thereines_ES


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