Digitalization of Cultural Heritage with Artificial Intelligence: Machine Learning and Deep Learning Solutions
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 20 July 2025 | Viewed by 302
Special Issue Editors
Interests: geomatics; GIS analysis; digital twins; UAV acquisition; digital photogrammetry; 3D modelling; cultural heritage; machine learning; virtual reality; augmented reality; remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: geomatics; built heritage; indoor and outdoor mobile mapping systems; high-resolution 3D models; segmentation; classification; reproductions of sculptural works; digital archives; reuse and sharing of 3D data; technologies applied to educational projects
Special Issues, Collections and Topics in MDPI journals
Interests: geomatics; mobile mapping; laser scanning; photogrammetry; remote sensing; navigation; data processing; machine learning; unmanned aerial vehicles; cultural heritage
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are pleased to invite you to submit original contributions on the topic of the Digitalization of CH (cultural heritage) with AI (artificial intelligence), with a particular reference to ML (machine learning) and DL (deep learning) solutions.
The Digitalization of CH represents a fundamental process for the conservation and fruition of cultural goods. Recent technological advances in Geomatics have allowed experts to improve the quality of the digitalization process on the basis of innovative survey technologies. At the same time, the recent development of ML and DL applications has allowed us to make a revolution in the field of segmentation and classification processes in bidimensional and tridimensional domains. This great effort offered by AI represents an innovative possibility for improvements in the CH digitalization process, opening new perspectives for valorization purposes.
This Special issue aims to collect high-quality papers dealing with new challenges related to the application and the integration of ML, DL, and Geomatics for innovative cultural heritage digitalization processes aimed at conservation and fruition purposes.
We look forward to receiving your contributions.
Dr. Marcello La Guardia
Dr. Valentina Bonora
Dr. Andrea Masiero
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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.
Keywords
- cultural heritage
- TLS
- photogrammetry
- machine learning
- deep learning
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