Machine Learning and Digital Heritage: The CEPROQHA Project Perspective

Abdelhak Belhi, Houssem Gasmi, Abdelaziz Bouras, Taha Alfaqheri, Akuha Solomon Aondoakaa, Abdul H. Sadka, Sebti Foufou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Through this paper, we aim at investigating the impact of artificial intelligence technologies on cultural heritage promotion and long-term preservation in terms of digitization effectiveness, attractiveness of the assets, and value empowering. Digital tools have been validated to yield sustainable and yet effective preservation for multiple types of content. For cultural data, however, there are multiple challenges in order to achieve sustainable preservation using these digital tools due to the specificities and the high-quality requirements imposed by cultural institutions. With the rise of machine learning and data science technologies, many researchers and heritage organizations are nowadays searching for techniques and methods to value and increase the reliability of cultural heritage digitization through machine learning. The present study investigates some of these initiatives highlighting their added value and potential future improvements. We mostly cover the aspects related to our context which is the long-term cost-effective digital preservation of the Qatari cultural heritage through the CEPROQHA project.

Original languageEnglish (US)
Title of host publication4th International Congress on Information and Communication Technology - ICICT 2019, London
EditorsXin-She Yang, Simon Sherratt, Nilanjan Dey, Amit Joshi
PublisherSpringer
Pages363-374
Number of pages12
ISBN (Print)9789813293427
DOIs
StatePublished - 2020
Event4th International Congress on Information and Communication Technology, ICICT 2019 - London, United Kingdom
Duration: Feb 27 2019Feb 28 2019

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1027
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference4th International Congress on Information and Communication Technology, ICICT 2019
CountryUnited Kingdom
CityLondon
Period2/27/192/28/19

Keywords

  • 3D-holoscopic imaging
  • Artificial intelligence
  • CEPROQHA project
  • Cultural heritage
  • Machine learning

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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  • Cite this

    Belhi, A., Gasmi, H., Bouras, A., Alfaqheri, T., Aondoakaa, A. S., Sadka, A. H., & Foufou, S. (2020). Machine Learning and Digital Heritage: The CEPROQHA Project Perspective. In X-S. Yang, S. Sherratt, N. Dey, & A. Joshi (Eds.), 4th International Congress on Information and Communication Technology - ICICT 2019, London (pp. 363-374). (Advances in Intelligent Systems and Computing; Vol. 1027). Springer. https://doi.org/10.1007/978-981-32-9343-4_29