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Introduction
Skills and Expertise
Additional affiliations
October 2019 - December 2022
Position
- PhD Student
Description
- PhD on Pain behavior analysis using Deep Learning
Publications
Publications (7)
After the fire that destroyed part of the cathedral Notre-Dame de Paris, a working group specialized in digital data coordinated a scientific project that would allow the management of all the digital data produced by scientific research activities along with restoration operations. The ERC advanced grant “nDame Heritage” project combines digital h...
After the catastrophic fire at Notre Dame de Paris, a significant challenge was presented by the numerous lead-contaminated remnants. To address this, a detailed digitization strategy was devised and executed, tailored to the unique needs of this extensive and diverse corpus. This strategy involved the development and customization of both hardware...
![Figure 4: Overview of CRMgeo and GeoSPARQL [13].](profile/Anais-Guillem-2/publication/375489449/figure/fig3/AS:11431281203882303@1699479553788/Overview-of-CRMgeo-and-GeoSPARQL-13_Q320.jpg)
![Figure 5: Schema representing the RCC8 [26] modified (translated).](profile/Anais-Guillem-2/publication/375489449/figure/fig4/AS:11431281203882304@1699479553953/Schema-representing-the-RCC8-26-modified-translated_Q320.jpg)
This work aims at the conceptual and ontological modeling of the abstract spatial relations in heterogeneous cultural heritage data. This work focuses on built heritage, studying the case of Notre-Dame de Paris. The spatial information is a transversal component across the metadata and paradata collection in the datasets about Notre-Dame. The integ...
The zero-shot performance of foundation models has captured a lot of attention. Specifically, the Segment Anything Model (SAM) has gained popularity in computer vision due to its label-free segmentation capabilities. Our study proposes using SAM on cultural heritage data, specifically images of Notre-Dame de Paris, with a controlled vocabulary. SAM...
