- Email: nicolas.boutry-at-lrde.epita.fr
- Tel: +33 6 76 80 10 53
Graduated from ESIEE Paris in 2002 in the field of Signal Processing and Telecommunications, Nicolas Boutry has spent over four years in Switzerland at EPFL where he did research on MR images of human brains and on image compression. He joined then a company called MyCO2 to work on pattern recognition. He realized his Ph.D. thesis on well-composed images from 2014 to 2016 at EPITA on the Olena project and at the LIGM at ESIEE Paris. He is now research assistant at EPITA, still on well-composed images and topological issues in nD discrete images.
My curriculum vitae is available HERE.
- Subject: Well-composed images
- Advisors: Thierry Géraud (LRDE)
- Algorithmics (TD / TP for 3rd-year students at EPITA)
- Regular Language Theory (TD / TP for 3rd-year students at EPITA)
- Rational Databases (TP for 3rd-year students at EPITA)
Nicolas Boutry, Thierry Géraud, Laurent Najman, An Equivalence Relation between Morphological Dynamics and Persistent Homology in 1D, ISMM 2019 PDF
Nicolas Boutry, Maria-Jose Jimenez, Rocio Gonzalez-Diaz, One more step towards well-composedness of cell complexes over nD pictures , DGCI 2019 PDF
Nicolas Boutry, Thierry Géraud, Laurent Najman, How to Make n-D Plain Maps Alexandrov-Well-Composed in a Self-dual Way, JMIV 2019 PDF
Nicolas Boutry, Maria-Jose Jimenez, Rocio Gonzalez-Diaz, Weakly well-composed cell complexes over nD pictures , Information Sciences 2018 PDF
Nicolas Boutry, Thierry Geraud, Laurent Najman, A Tutorial on Well-Composedness, JMIV 2017 PDF
Nicolas Boutry, Thierry Geraud, Laurent Najman, Well-Composedness in Alexandrov Spaces Implies Digital Well-Composedness in Z^n, DGCI 2017 PDF
Nicolas Boutry, Thierry Geraud, Laurent Najman, About the equivalence between AWCness and DWCness, HAL 2016 PDF