Rémi Flamary
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Projet AMOR
Description
Le but de ce projet est de proposer des méthodes automatiques d’extraction d’information dans des séries d’images de télédétection à haute résolution temporelle. Ces méthodes prendront en compte les propriétés intrinsèques des images multitemporelles : échantillonage temporel irrégulier, image multicomposante et grande masse de données. Elles devront de plus fournir des modèles interprétables qui pourrons être mis à jour itérativement.
Le Projet AMOR est un projet Jeunes Chercheurs soutenu par le GdR 720 ISIS et l’association GRETSI.
Responsables et partenaires du projet
- Rémi Flamary (Responsable), Laboratoire Lagrange,
- Mauro Dalla Mura (Co-responsable), GIPSA-Lab
- Guillaume Tochon, GIPSA-Lab
- Silvia Valero-Valbuena (Porteur), CESBIO
- Mathieu Fauvel (Porteur), DYNAFOR
- Anthony Zullo, DYNAFOR
News
Kickoff Meeting
15 Octobre 2013
Nous nous sommes rencontré à Nice à la suite du Workshop MAHI pour amorcer nos collaborations scientifiques.
Publications
| R. Flamary, M. Fauvel, M. Dalla Mura, S. Valero, Analysis of multi-temporal classification techniques for forecasting image times series, Geoscience and Remote Sensing Letters (GRSL), Vol. 12, N. 5, pp 953-957, 2015. |
| Abstract: The classification of an annual times series by using data from past years is investigated in this paper. Several classification schemes based on data fusion, sparse learning and semi-supervised learning are proposed to address the problem. Numerical experiments are performed on a MODIS image time series and show that while several approaches have statistically equivalent performances, SVM with 1 regularization leads to a better interpretation of the results due to their inherent sparsity in the temporal domain. |
BibTeX:
@article{flamary2014analysis,
author = { Flamary, R. and Fauvel, M. and Dalla Mura, M. and Valero, S.},
title = {Analysis of multi-temporal classification techniques for forecasting image times series},
journal = { Geoscience and Remote Sensing Letters (GRSL)},
volume = {12},
number = {5},
pages = {953-957},
year = {2015}
} |
| R. Flamary, I. Harrane, M. Fauvel, S. Valero, M. Dalla Mura, Discrimination périodique à partir d’observations multi-temporelles, GRETSI, 2015. |
| Abstract: In this work, we propose a novel linear classification scheme for non-stationary periodic data. We express the classifier in a temporal basis while regularizing its temporal complexity leading to a convex optimization problem. Numerical experiments show very good results on a simulated example and on real life remote sensing image classification problem. |
BibTeX:
@conference{flamary2015discrimination,
author = {Flamary, R. and Harrane, I. and Fauvel, M. and Valero, S. and Dalla Mura, M.},
title = {Discrimination périodique à partir d’observations multi-temporelles},
booktitle = {GRETSI},
year = {2015}
} |