Simon Boutet
Recently graduated from the Faculty of Architecture of ULiège (2025), Simon Boutet has developed an interest in the preservation of built heritage and the integration of digital tools into visual inspection methods. His master's thesis explores the potential of artificial intelligence and deep learning networks in the detection and classification of surface defects based on images from photographic surveys. This dissertation, completed under the supervision of Prof. Pierre Hallot, allowed him to combine approaches from computer vision and architectural documentation.
Building on this research, he is now pursuing a doctoral thesis at the same university, again under the supervision of Prof. Pierre Hallot. This research focuses on improving methods for acquiring and analyzing historic buildings using artificial intelligence, by exploring the combination of different visual representations of pathologies, particularly through the use of multispectral imaging (RGB, infrared, etc.). The goal of this research is to optimize visual inspection protocols for cultural heritage by leveraging the potential of artificial intelligence, while enhancing its interoperability with current heritage documentation methods, such as photogrammetry and laser scanning.
Research Interests : Built Heritage / Artificial Intelligence / Architectural Diagnostics / Deep Learning / Computer Vision / Photogrammetry / Documentation
Simon Boutet's Publications
; Noël, Ophélie ; Boutet, Simon et al.
; Noël, Ophélie ; Hallot, Pierre et al.
