AI Innovation in Cultural Heritage Preservation: Bridging Technology, Image, and Tradition

Dear Colleagues,

Artificial intelligence (AI) is redefining the practices and studies concerning the connection between cultural heritage and images. AI research is engendering reflections and transformations in the development of activities comprising the processes of musealization and patrimonialization, particularly concerning conservation, documentation, and communication actions that utilize images as a foundational component in their methodologies. These innovations are facilitating advancements in various fields, including damage monitoring and diagnosis for heritage preservation, the production of high-fidelity 3D models of cultural assets, and the automatic classification of elements that characterize these heritages. This research, especially interdisciplinary research, is also prompting discussions about the positive and negative consequences of these advances, with implications for professional ethics and research involving AI, images, and cultural heritage, both tangible and intangible.

The objective of this Special Issue is to present contributions, namely of an interdisciplinary nature, aligned with the following thematic directions:

• Articles that present findings regarding the applications of AI in the convergence between image and cultural heritage;
• Articles that present a discussion of the concepts that are affected by the transformations that result from the application of innovations in AI to the study of images in the context of cultural heritage;
• Articles that engage in critical discourse on the social, political, and ethical implications of AI in the domains of image and heritage studies.
• The scope of contributions may encompass, but is not limited to, the following topics:
• AI and images for the preservation and promotion of tangible and intangible cultural heritage;
• The study of IA and the visual representation of objects and artifacts within the context of museums and heritage spaces;
• The investigation of machine learning and deep learning as applied to the domain of image studies and cultural heritage;
• The use of AI in the creation of three-dimensional (3D) models of cultural assets;
• The application of Neural Radiance Fields (NeRF) for the reproduction of cultural heritage objects;
• AI, remote sensing technologies, and heritage images;
• Computer vision and heritage image processing;
• Convolutional neural networks (CNNs) in the identification and recognition of patterns in heritage images;
• The use of AI and imagery in the process of conserving or restoring cultural heritage;
• The application of AI and images in the context of heritage documentation or communication.
• The application of artificial intelligence (AI) and the use of images in the field of heritage education;
• The use of AI, crowdsourcing, and collaborative processes for sharing heritage images.
• The application of generative AI to the creation of images and the generation of synthetic memories of cultural heritage;
• AI, visual arts, and cultural heritage;
• The nexus of ethics and AI at the interface between image and heritage;
• Public policies, social actions, and good practices for AI in the convergence between image and heritage.

Dr. Carmen Silva
Prof. Dr. Lídia Oliveira Silva
Dr. Ana Carla Amaro
Dr. Vittoria Guglielmi
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Heritage is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.