Difference between revisions of "Jobs/M2 TG 2020 DeepLearning Imagerie Hyperspectrale"

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|Reference id=M2 TG 2020 DeepLearning Imagerie Hyperspectrale
 
|Reference id=M2 TG 2020 DeepLearning Imagerie Hyperspectrale
 
|Title=Apprentissage de dynamique temporelle pour le démélange de séquences d’images hyperspectrales
 
|Title=Apprentissage de dynamique temporelle pour le démélange de séquences d’images hyperspectrales
|Dates=5 - 6 mois
+
|Dates=5 - 6 mois (2020)
 
|Research field=Traitement d'Images
 
|Research field=Traitement d'Images
 
|Related project=Olena
 
|Related project=Olena
 
|Advisor=Guillaume Tochon
 
|Advisor=Guillaume Tochon
|Objectives=Tous les détails concernant le sujet de stage sont ici -> https://www.lrde.epita.fr/~gtochon/stage/fiche_poste_stage_apprentissage_resnet_teledetection.pdf
+
|Objectives=https://www.lrde.epita.fr/~gtochon/stage/fiche_poste_stage_apprentissage_resnet_teledetection.pdf
  +
|Contact=guillaume.tochon@lrde.epita.fr
|References=[1] J. M. Bioucas-Dias, A. Plaza, G. Camps-Valls, P. Scheunders, N. Nasrabadi, and J. Chanussot, “Hyperspectral
 
remote sensing data analysis and future challenges,” IEEE Geoscience and remote sensing magazine, vol. 1, no. 2,
 
pp. 6–36, 2013.
 
[2] J. M. Bioucas-Dias, A. Plaza, N. Dobigeon, M. Parente, Q. Du, P. Gader, and J. Chanussot, “Hyperspectral
 
unmixing overview: Geometrical, statistical, and sparse regression-based approaches,” IEEE journal of selected
 
topics in applied earth observations and remote sensing, vol. 5, no. 2, pp. 354–379, 2012.
 
[3] M. A. Goenaga, M. C. Torres-Madronero, M. Velez-Reyes, S. J. Van Bloem, and J. D. Chinea, “Unmixing analysis
 
of a time series of hyperion images over the gu´anica dry forest in puerto rico,” IEEE Journal of Selected Topics
 
in Applied Earth Observations and Remote Sensing, vol. 6, no. 2, pp. 329–338, 2012.
 
[4] Y. LeCun, Y. Bengio, and G. Hinton, “Deep learning,” nature, vol. 521, no. 7553, p. 436, 2015.
 
[5] R. Fablet, S. Ouala, and C. Herzet, “Bilinear residual neural network for the identification and forecasting of
 
dynamical systems,” arXiv preprint arXiv:1712.07003, 2017.
 
[6] D. Nguyen, S. Ouala, L. Drumetz, and R. Fablet, “Em-like learning chaotic dynamics from noisy and partial observations,” arXiv preprint arXiv:1903.10335, 2019.
 
[7] F. Rousseau, L. Drumetz, and R. Fablet, “Residual networks as flows of diffeomorphisms,” Journal of Mathematical Imaging and Vision, pp. 1–11, 2019.
 
|Contact=<guillaume . tochon at lrde . epita . fr>
 
 
|Compensation=1000 euros bruts/mois
 
|Compensation=1000 euros bruts/mois
 
|Type=Master Internship
 
|Type=Master Internship
|Language=fr
+
|Language=en
 
|Published=Yes
 
|Published=Yes
 
}}
 
}}

Latest revision as of 17:20, 21 October 2019

Apprentissage de dynamique temporelle pour le démélange de séquences d’images hyperspectrales
Reference id

M2 TG 2020 DeepLearning Imagerie Hyperspectrale

Dates

5 - 6 mois (2020)

Research field

Traitement d'Images

Related project

Olena

Advisor

Guillaume Tochon

General presentation of the field
Prerequisites
Objectives

https://www.lrde.epita.fr/~gtochon/stage/fiche_poste_stage_apprentissage_resnet_teledetection.pdf

Benefit for the candidate
References
Place LRDE: How to get to us
Compensation

1000 euros bruts/mois

Future work opportunities
Contact

guillaume.tochon@lrde.epita.fr