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Andrew Caunes

PhD Student - LS2N - Centrale Nantes


Welcome to my page ! I'm a PhD student at LS2N, Centrale Nantes (ARMEN team).
My research interests lie primarily in machine learning, and more specifically in deep learning.

My thesis is about developing and applying deep learning methods for the analysis of road infrastructure based on visual data : 2D images, 3D LiDAR point clouds, ...

Currently, I'm focusing on self-supervised methods and the use of vision foundation models in order to achieve satisfying performance with minimal annotation in the most scalable way possible.


point cloud
Multiple concatenated LiDAR scans from our sensors at Logiroad






Poster PhD thesis: Multi-sensor semantic segmentation through deep learning: application to the analysis of the state of road infrastructures

Andrew Caunes1,2    Thierry Chateau 1    Vincent Frémont2   
1 Logiroad   2 Centrale Nantes, LS2N - Laboratoire des Sciences du Numérique de Nantes  


state of the art




Traffic sign localization by triangulation through sequential detection and classification

Andrew Caunes1,3    Philippe Balmas1,2    Loïc Alizon1    Abir Gazzah1,2    Thierry Chateau1 Vincent Frémont3
1 Logiroad   2 Université Clermont Auvergne   3 Centrale Nantes, LS2N - Laboratoire des Sciences du Numérique de Nantes  


pipeline




Digital twins of human corneal endothelium from generative adversarial networks

Eloi Dussy Lachaud1    Andrew Caunes1    Gilles Thuret2    Yann Gavet1   
1 Mines Saint-Etienne, Univ. Lyon, CNRS, UMR 5307 LGF, Centre SPIN, F - 42023 Saint-Etienne, France.   2 Laboratoire Biologie, ingénierie et imagerie de la Greffe de Cornée (BiiGC), Faculté de Médecine, Campus Santé Innovation, Université Jean Monnet, Saint-Etienne, France  


cells