Pentru varianta în română, apăsați aici.
Grant: 178PCE/2021, PN-III-P4-ID-PCE-2020-0788
Contracting authority: UEFISCDI
Grant value: 1.198.032 RON
Coordinating institution: Romanian Institute of Science and Technology
Supported by: Oltenia Museum, Restoration and Conservation Lab, History and Archaeology Section
Implementation period: 04.01.2021-31.12.2023
Obtained results
Chemical and corrosion determination
Semantic inpainting and 3D reconstruction
The OPERA project aimed to show how artificial intelligence (deep learning) can offer support towards the restoration of deteriorated cultural heritage assets and exposition of a digital counterpart for the objects.
A deep learning regression model can first estimate the chemical composition at the surface of the object from microscope images. Subsequently, the present corrosion compounds can be delineated and identified through a semantic segmentation model. At this point, the expert can also consider the output from this virtual assistant and proceed with the appropriate treatment for the piece.
Once the chemical repair is achieved, the artistic completion must be performed. At this second stage, a semantic inpainting technique can offer different plausible completions to the expert. Based on this agreed output, a 3D generative model can virtually produce a replica of the object.
Discover how deep learning models guide restoration processes, offering a glimpse into the future of preservation: