Show simple item record

dc.contributor.authorLlamas Fernández, José María 
dc.contributor.authorMartín Lerones, Pedro 
dc.contributor.authorZalama Casanova, Eduardo 
dc.contributor.authorGómez García-Bermejo, Jaime 
dc.date.accessioned2016-11-23T11:49:28Z
dc.date.available2016-11-23T11:49:28Z
dc.date.issued2016
dc.identifier.citationMarinos Ioannides, Eleanor Fink, Antonia Moropoulou, Monika Hagedorn-Saupe, Antonella Fresa, Gunnar Liestøl, Vlatka Rajcic, Pierre Grussenmeyer (Eds.). EuroMed 2016: Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection. Nicosia, Cyprus, 31 october – 5 november, 2016. Springer International publishing, 2016es
dc.identifier.isbn978-3-319-48974-2es
dc.identifier.urihttp://uvadoc.uva.es/handle/10324/21074
dc.descriptionProducción Científicaes
dc.description.abstractThe digital documentation of cultural heritage (CH) often requires interpretation and classification of a huge amount of images. The INCEPTION European project focuses on the development of tools and methodologies for obtaining 3D models of cultural heritage assets, enriched by semantic information and integration of both parts on a new H-BIM (Heritage - Building Information Modeling) platform. In this sense, the availability of automated techniques that allow the interpretation of photos and the search using semantic terms would greatly facilitate the work to develop the project. In this article the use of deep learning techniques, specifically the convolutional neural networks (CNNs) for analyzing images of cultural heritage is assessed. It is considered that the application of these techniques can make a significant contribution to the objectives sought in the INCEPTION project and, more generally, the digital documentation of cultural heritage.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherSpringer International Publishing AGes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectPatrimonio culturales
dc.subjectInformación electrónicaes
dc.titleApplying Deep Learning Techniques to Cultural Heritage Images Within the INCEPTION Projectes
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.identifier.doi10.1007/978-3-319-48974-2_4es
dc.relation.publisherversionhttp://rd.springer.com/chapter/10.1007/978-3-319-48974-2_4es
dc.title.eventEuroMed 2016: Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection. Part Ies
dc.description.projectJunta de Castilla y León (Programa de apoyo a proyectos de investigación-Ref. VA036U14)es
dc.description.projectJunta de Castilla y León (programa de apoyo a proyectos de investigación - Ref. VA013A12-2)es
dc.description.projectMinisterio de Economía, Industria y Competitividad (Grant DPI2014-56500-R)
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record