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Applying Deep Learning Techniques to Cultural Heritage Images Within the INCEPTION Project

机译:在INCEPTION项目中将深度学习技术应用于文化遗产图像

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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.
机译:文化遗产(CH)的数字文档通常需要对大量图像进行解释和分类。欧洲INCEPTION项目着重于开发工具和方法,以获取文化遗产资产的3D模型,并通过语义信息以及将这两个部分集成在新的H-BIM(遗产-建筑信息模型)平台上而得到丰富。在这种意义上,允许使用语义术语解释照片和进行搜索的自动化技术的可用性将极大地促进项目开发工作。在本文中,评估了深度学习技术(特别是卷积神经网络(CNN))用于分析文化遗产图像的用途。人们认为,这些技术的应用可以为INCEPTION项目寻求的目标做出重要贡献,更广泛地说,可以为文化遗产的数字文献做出贡献。

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