Artificial Intelligence at the Interface between Cultural Heritage and Photography: A Systematic Literature Review

IF 2 0 HUMANITIES, MULTIDISCIPLINARY Heritage Pub Date : 2024-07-17 DOI:10.3390/heritage7070180
Carmen Silva, Lídia Oliveira
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Abstract

Artificial intelligence has inspired a significant number of studies on the interface between cultural heritage and photography. The aims of these studies are, among others, to streamline damage monitoring or diagnoses for heritage preservation, enhance the production of high-fidelity 3D models of cultural assets, or improve the analysis of heritage images using computer vision. This article presents the results of a systematic literature review to highlight the recent state of these studies, published in the last five years and available in the Scopus, Web of Science, and JSTOR databases. The aim is to identify the potential and challenges of artificial intelligence through the connection between cultural heritage and photography, the latter of which represents a relevant methodological aspect in these investigations. In addition to the advances exemplified, the vast majority of studies indicate that there are also many obstacles to overcome. In particular, there is a need to improve artificial intelligence methods that still have significant flaws. These include inaccuracy in the automatic classification of images and limitations in the applications of the results. This article also aims to reflect on the meaning of these innovations when considering the direction of the relationship between cultural heritage and photography.
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文化遗产与摄影之间的人工智能:系统性文献综述
人工智能激发了大量关于文化遗产与摄影之间关系的研究。这些研究的目的包括:简化遗产保护的损坏监测或诊断,增强文化资产高保真三维模型的制作,或利用计算机视觉改进对遗产图像的分析。本文介绍了系统性文献综述的结果,重点介绍了过去五年中发表的、可在 Scopus、Web of Science 和 JSTOR 数据库中找到的这些研究的最新情况。其目的是通过文化遗产与摄影之间的联系来确定人工智能的潜力和挑战,后者是这些研究的一个相关方法论方面。除了所展示的进步之外,绝大多数研究表明,还有许多障碍需要克服。特别是,人工智能方法仍存在重大缺陷,需要加以改进。这些缺陷包括图像自动分类的不准确性和结果应用的局限性。本文还旨在思考这些创新在考虑文化遗产与摄影之间关系的发展方向时所具有的意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Heritage
Heritage Multiple-
CiteScore
2.90
自引率
17.60%
发文量
165
审稿时长
10 weeks
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