User

Nicolas Boutry

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Contact

  • Email: nicolas.boutry-at-lrde.epita.fr
  • Tel: +33 6 76 80 10 53

Short bio

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.

Current status

Research Associate:

  • Subject: A.I. applied to biomedical images, Well-composed images.
  • Advisors: Thierry Géraud (LRDE)

Teaching:

  • 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)
  • Video Compression (5th-year students at EPITA)
  • Wavelets Theory (5th-year students at EPITA)
  • Deep Learning (5th-year students at EPITA)

Publications

Nicolas Boutry, Rocio Gonzalez-Diaz, Maria-Jose Jimenez, Eduardo Paluzo-Hildago, Euler Well-Composedness, IWCIA 2020 PDF

Nicolas Boutry, Rocio Gonzalez-Diaz, Laurent Najman, Thierry Géraud, A 4D counter-example showing that DWCness does not imply CWCness in n-D, IWCIA 2020 PDF

Michael Atlan, Julie Rivet, Antoine Taliercio, Nicolas Boutry, Guillaume Tochon, Jean-Pierre Huignard, Experimental digital Gabor hologram rendering of C. elegans worms by a model-trained convolutional neural network', SPIE Photonics 2020

Zhou Zhao, Nicolas Boutry, Elodie Puybareau, Thierry Géraud, A Two-Stage Temporal-Like Fully Convolutional Network Framework for Left Ventricle Segmentation and Quantification on MR Images, LVQuan 2019 PDF

Nicolas Boutry, Joseph Chazalon, Elodie Puybareau, Guillaume Tochon, Hugues Talbot, Thierry Géraud, Using separated inputs for multimodal brain tumor segmentation with 3D U-Net-like architectures, BraTS 2019 PDF

Le Duy Huynh , Nicolas Boutry , Thierry Geraud, Connected Filters on Generalized Shape-Spaces,PRL 2019 PDF

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

Edwin Carlinet, Yongchao Xu, Nicolas Boutry, Thierry Géraud, La pseudo-distance du Dahu, ORASIS 2017 PDF

Thierry Géraud, Yongchao Xu, Edwin Carlinet, Nicolas Boutry, Introducing the Dahu Pseudo-Distance, ISMM PDF

Nicolas Boutry, Thierry Geraud, Laurent Najman, About the equivalence between AWCness and DWCness, HAL 2016 PDF

Nicolas Boutry, Thierry Geraud, Laurent Najman, How to Make nD Images Well-Composed Without Interpolation, ICIP 2015 PDF (dedicated page: Publications/boutry.15.icip)

Nicolas Boutry, Thierry Geraud, Laurent Najman, How to Make nD Functions Digitally Well-Composed in a Self-Dual Way, ISMM 2015 PDF (dedicated page: Publications/boutry.15.ismm)

Nicolas Boutry, Thierry Geraud, Laurent Najman, Une généralisation du bien-composé à la dimension n, GTGéoDis 2014 PDF, Poster (dedicated page: Publications/boutry.14.geodis)

Nicolas Boutry, Thierry Geraud, Laurent Najman, On Making nD Images Well-Composed by a Self-Dual Local Interpolation, DGCI 2014 PDF (dedicated page: Publications/boutry.14.dgci)

Link to my PhD report

A Study of Well-composedness in n-D