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Título
Applying Deep Learning Techniques to Cultural Heritage Images Within the INCEPTION Project
Autor
Congreso
EuroMed 2016: Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection. Part I
Año del Documento
2016
Editorial
Springer International Publishing AG
Descripción
Producción Científica
Documento Fuente
Marinos 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, 2016
Abstract
The 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.
Materias (normalizadas)
Patrimonio cultural
Información electrónica
ISBN
978-3-319-48974-2
Patrocinador
Junta de Castilla y León (Programa de apoyo a proyectos de investigación-Ref. VA036U14)
Junta de Castilla y León (programa de apoyo a proyectos de investigación - Ref. VA013A12-2)
Ministerio de Economía, Industria y Competitividad (Grant DPI2014-56500-R)
Junta de Castilla y León (programa de apoyo a proyectos de investigación - Ref. VA013A12-2)
Ministerio de Economía, Industria y Competitividad (Grant DPI2014-56500-R)
Version del Editor
Idioma
eng
Derechos
openAccess
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