1 code implementation • 18 Aug 2023 • Camille Ruppli, Pietro Gori, Roberto Ardon, Isabelle Bloch
Early diagnosis of prostate cancer is crucial for efficient treatment.
no code implementations • 27 Jul 2022 • Camille Ruppli, Pietro Gori, Roberto Ardon, Isabelle Bloch
Following previous works that introduce a small amount of supervision, we propose a framework to find optimal transformations for contrastive learning using a differentiable transformation network.
no code implementations • 21 Jun 2021 • Martin Charachon, Paul-Henry Cournède, Céline Hudelot, Roberto Ardon
We show that visual explanation can be produced as the difference between two generated images obtained via two specific conditional generative models.
no code implementations • 14 Dec 2020 • Martin Charachon, Céline Hudelot, Paul-Henry Cournède, Camille Ruppli, Roberto Ardon
From a given classifier, we train two generators to produce from an input image the so called similar and adversarial images.
no code implementations • 16 Jan 2017 • Hadrien Bertrand, Matthieu Perrot, Roberto Ardon, Isabelle Bloch
Improving the model is not an easy task, due to the large number of hyper-parameters governing both the architecture and the training of the network, and to the limited understanding of their relevance.