2 citations · 2 across the 3 of their papers we have counts for
6 papers
Deep Learning methods for automatic evaluation of delayed enhancement-MRI. The results of the EMIDEC challenge
Alain Lalande, Zhihao Chen, Thibaut Pommier +30
A key factor for assessing the state of the heart after myocardial infarction (MI) is to measure whether the myocardium segment is viable after reperfusion or revascularization the…
P2D: a self-supervised method for depth estimation from polarimetry
Marc Blanchon, Désiré Sidibé, Olivier Morel +3
Monocular depth estimation is a recurring subject in the field of computer vision. Its ability to describe scenes via a depth map while reducing the constraints related to the form…
Segmentation of the Myocardium on Late-Gadolinium Enhanced MRI based on 2.5 D Residual Squeeze and Excitation Deep Learning Model
Abdul Qayyum, Alain Lalande, Thomas Decourselle +3
Cardiac left ventricular (LV) segmentation from short-axis MRI acquired 10 minutes after the injection of a contrast agent (LGE-MRI) is a necessary step in the processing allowing…
Polarimetric image augmentation
Marc Blanchon, Olivier Morel, Fabrice Meriaudeau +2
Robotics applications in urban environments are subject to obstacles that exhibit specular reflections hampering autonomous navigation. On the other hand, these reflections are hig…
Road scenes analysis in adverse weather conditions by polarization-encoded images and adapted deep learning
Rachel Blin, Samia Ainouz, Stéphane Canu +1
Object detection in road scenes is necessary to develop both autonomous vehicles and driving assistance systems. Even if deep neural networks for recognition task have shown great…
MFCC-based Recurrent Neural Network for Automatic Clinical Depression Recognition and Assessment from Speech
Emna Rejaibi, Ali Komaty, Fabrice Meriaudeau +2
Clinical depression or Major Depressive Disorder (MDD) is a common and serious medical illness. In this paper, a deep recurrent neural network-based framework is presented to detec…