| 2008 |
|---|
| 7 | EE | Radhouène Neji,
Gilles Fleury,
Jean Francois Deux,
Alain Rahmouni,
Guillaume Bassez,
Alexandre Vignaud,
Nikos Paragios:
Support vector driven Markov random fields towards DTI segmentation of the human skeletal muscle.
ISBI 2008: 923-926 |
| 2007 |
|---|
| 6 | EE | Radhouène Neji,
Noura Azzabou,
Nikos Paragios,
Gilles Fleury:
A Convex Semi-definite Positive Framework for DTI Estimation and Regularization.
ISVC (1) 2007: 220-229 |
| 2006 |
|---|
| 5 | EE | Maïza Bekara,
Luc Knockaert,
Abd-Krim Seghouane,
Gilles Fleury:
A model selection approach to signal denoising using Kullback's symmetric divergence.
Signal Processing 86(7): 1400-1409 (2006) |
| 2005 |
|---|
| 4 | EE | Abd-Krim Seghouane,
Maïza Bekara,
Gilles Fleury:
A criterion for model selection in the presence of incomplete data based on Kullback's symmetric divergence.
Signal Processing 85(7): 1405-1417 (2005) |
| 2004 |
|---|
| 3 | | Alfred O. Hero,
Sepidarseh Zareparsi,
Anand Swaroop,
Gilles Fleury:
Pareto Depth Sampling Distributions for Gene Ranking.
ISBI 2004: 65-68 |
| 2 | EE | Abd-Krim Seghouane,
Yassir Moudden,
Gilles Fleury:
Regularizing the effect of input noise injection in feedforward neural networks training.
Neural Computing and Applications 13(3): 248-254 (2004) |
| 1 | EE | Alfred O. Hero,
Gilles Fleury:
Pareto-Optimal Methods for Gene Ranking.
VLSI Signal Processing 38(3): 259-275 (2004) |
