2026-04-27T22:05:46Zhttps://uvadoc.uva.es/oai/request
oai:uvadoc.uva.es:10324/210742025-02-17T13:32:45Zcom_10324_1168com_10324_931com_10324_894col_10324_1304
UVaDOC author Llamas Fernández, José María author Martín Lerones, Pedro author Zalama Casanova, Eduardo author Gómez García-Bermejo, Jaime 2016-11-23T11:49:28Z 2016-11-23T11:49:28Z 2016 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 978-3-319-48974-2 http://uvadoc.uva.es/handle/10324/21074 10.1007/978-3-319-48974-2_4 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. eng Attribution-NonCommercial-NoDerivatives 4.0 International Patrimonio cultural Información electrónica Applying Deep Learning Techniques to Cultural Heritage Images Within the INCEPTION Project info:eu-repo/semantics/conferenceObject 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