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.
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Acknowledgements
This research project has received funding from the EU’s H2020 Reflective framework programme for research and innovation under grant agreement no. 665220. This work was also supported by the Ministry of Science and Innovation, fundamental research project ref. DPI2014-56500 and Junta de Castilla y León ref. VA036U14.
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Llamas, J., Lerones, P.M., Zalama, E., Gómez-García-Bermejo, J. (2016). Applying Deep Learning Techniques to Cultural Heritage Images Within the INCEPTION Project. In: Ioannides, M., et al. Digital Heritage. Progress in Cultural Heritage: Documentation, Preservation, and Protection. EuroMed 2016. Lecture Notes in Computer Science(), vol 10059. Springer, Cham. https://doi.org/10.1007/978-3-319-48974-2_4
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DOI: https://doi.org/10.1007/978-3-319-48974-2_4
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