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

机译:将深入学习技术应用于初始化项目中的文化遗产图像

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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解释和分类大量图像。成立欧洲项目侧重于开发用于获取文化遗产资产3D模型的工具和方法,通过语义信息丰富,并在新的H-BIM(遗产建筑信息建模)平台上的两部分集成。从这个意义上讲,自动化技术的可用性允许照片和搜索使用语义术语来促进开发项目的工作。在本文中,评估了使用深度学习技术,特别是用于分析文化遗产图像的卷积神经网络(CNNS)。据认为,这些技术的应用可以对初始项目中寻求的目标作出重大贡献,更普遍地是文化遗产的数字文件。

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