no code implementations • 8 Apr 2021 • Jorge F. Lazo, Sara Moccia, Aldo Marzullo, Michele Catellani, Ottavio De Cobelli, Benoit Rosa, Michel de Mathelin, Elena De Momi
In this work we study the implementation of 3 different Convolutional Neural Networks (CNNs), using a 2-steps training strategy, to classify images from the urinary tract with and without lesions.
no code implementations • 5 Apr 2021 • Jorge F. Lazo, Aldo Marzullo, Sara Moccia, Michele Catellani, Benoit Rosa, Michel de Mathelin, Elena De Momi
Of these, two architectures are taken as core-models, namely U-Net based in residual blocks($m_1$) and Mask-RCNN($m_2$), which are fed with single still-frames $I(t)$.
no code implementations • 13 Jan 2021 • Jorge F. Lazo, Aldo Marzullo, Sara Moccia, Michele Catellani, Benoit Rosa, Michel de Mathelin, Elena De Momi
For the training of these networks, we analyze the use of two different color spaces: gray-scale and RGB data images.
no code implementations • 21 Oct 2019 • Francesco Calimeri, Francesco Cauteruccio, Luca Cinelli, Aldo Marzullo, Claudio Stamile, Giorgio Terracina, Francoise Durand-Dubief, Dominique Sappey-Marinier
The framework relies on a combined use of ML and ASP, and is general enough to be applied in several other application scenarios, which are outlined in the paper.