17 citations · 19 across the 6 of their papers we have counts for
4 papers · 1 filter
Discretely-constrained deep network for weakly supervised segmentation
Jizong Peng, Hoel Kervadec, Jose Dolz +3
An efficient strategy for weakly-supervised segmentation is to impose constraints or regularization priors on target regions. Recent efforts have focused on incorporating such cons…
Constrained domain adaptation for Image segmentation
Mathilde Bateson, Jose Dolz, Hoel Kervadec +2
We propose to adapt segmentation networks with a constrained formulation, which embeds domain-invariant prior knowledge about the segmentation regions. Such knowledge may take the…
Curriculum semi-supervised segmentation
Hoel Kervadec, Jose Dolz, Eric Granger +1
This study investigates a curriculum-style strategy for semi-supervised CNN segmentation, which devises a regression network to learn image-level information such as the size of a…
Constrained Deep Networks: Lagrangian Optimization via Log-Barrier Extensions
Hoel Kervadec, Jose Dolz, Jing Yuan +3
This study investigates imposing hard inequality constraints on the outputs of convolutional neural networks (CNN) during training. Several recent works showed that the theoretical…