AI meets Heritage Science at IESL-FORTH

We are thrilled to announce our pioneering publication:
“Machine learning assisted real-time acoustic monitoring of laser cleaning in Heritage conservation.”
by G. D. Barmparis, A.-N. Raikidis, K. Melessanaki, G. P. Tsironis, G. J. Tserevelakis, and P. Pouli.

This study marks the beginning of a new era in laser cleaning for Heritage conservation — the first feasibility study demonstrating how real-time acoustic monitoring combined with explainable machine learning can guide conservators to take informed decisions for safe and precise restoration of sensitive cultural heritage objects.
By analyzing the acoustic signals generated during laser cleaning, our approach identifies the exact laser pulse that completely removes unwanted paint layers without harming the original substrate.

This work paves the way for smart, informed, data-driven restoration technologies, merging AI innovation with the preservation of cultural heritage — where science and heritage converge.

Read the full article: https://doi.org/10.1038/s40494-025-02146-3

Also in our institute news: https://www.iesl.forth.gr/en/ai-meets-heritage-science-institute-electronic-structure-laser-iesl-forth