Applying deep learning techniques to cultural heritage images within the INCEPTION project

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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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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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10059 LNCS, pp. 25–32). Springer Verlag. https://doi.org/10.1007/978-3-319-48974-2_4

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