Thierry Sedran
Papers
1
Total Citations
2
H-Index
1
About
Thierry Sedran is a researcher at the forefront of integrating computer vision and deep learning with urban infrastructure management. His primary research areas include automated infrastructure inspection, UAV-based remote sensing, and the application of advanced object detection methods to civil engineering challenges. Sedran’s most notable contribution is his pioneering work on the localization of Removable Urban Pavement Elements (RUPs) using unmanned aerial vehicles. In his highly cited 2024 paper, he introduced a novel deep learning framework built on the YOLOv8 architecture, designed to autonomously detect and map RUPs from UAV imagery. This innovation directly addresses the practical need for efficient maintenance of pavements that can be quickly opened and closed with lightweight equipment, offering a significant leap in automating urban asset management. While his work is still early in its citation lifecycle, its immediate impact is evident in its adoption by peers, and it positions Sedran as a key innovator in smart city technologies, blending robotics, AI, and civil engineering to solve real-world urban problems.
Research Focus
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Top Papers
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