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May 7, 2026Peer Community In Archaeology0 citationsOpen Access

Author response of: Towards an Easy-to-Use Machine Learning Framework for Cultural Heritage Scientists. Round#2

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CCChristos ChatzisavvasTPThomas PappasPRPanagiotis Rigas

Key Points

  • This recommendation aims to enhance the application of machine learning for cultural heritage professionals.
  • Proposed a user-friendly framework designed for cultural heritage scientists to facilitate the use of machine learning.
  • Included feedback from experts to refine the framework and increase practicality.
  • Demonstrated the framework's potential to streamline the integration of machine learning in cultural heritage projects.
  • Shown to improve the accessibility of advanced analytical tools for scientists in cultural heritage.

Abstract

A recommendation of: Christos Chatzisavvas, Thomas Pappas, Panagiotis Rigas, Nikolaos Mitianoudis, George Pavlidis, Chairi Kiourt, Anestis Koutsoudis, Vassilis Katsouros, and George Ioannakis Towards an Easy-to-Use Machine Learning Framework for Cultural Heritage Scientists https://doi.org/10.5281/zenodo.19856328

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Cite This Study

Chatzisavvas et al. (2026) studied this question.

synapsesocial.com/papers/69fbe357164b5133a91a293dhttps://doi.org/10.24072/pci.archaeo.100629.ar2
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