106 citations · 191 across the 6 of their papers we have counts for
6 papers
Addressing Failure Prediction by Learning Model Confidence
Charles Corbière, Nicolas Thome, Avner Bar-Hen +2
Assessing reliably the confidence of a deep neural network and predicting its failures is of primary importance for the practical deployment of these models. In this paper, we prop…
MUREL: Multimodal Relational Reasoning for Visual Question Answering
Remi Cadene, Hedi Ben-younes, Matthieu Cord +1
Multimodal attentional networks are currently state-of-the-art models for Visual Question Answering (VQA) tasks involving real images. Although attention allows to focus on the vis…
M2CAI Workflow Challenge: Convolutional Neural Networks with Time Smoothing and Hidden Markov Model for Video Frames Classification
Rémi Cadène, Thomas Robert, Nicolas Thome +1
Our approach is among the three best to tackle the M2CAI Workflow challenge. The latter consists in recognizing the operation phase for each frames of endoscopic videos. In this te…
Gossip training for deep learning
Michael Blot, David Picard, Matthieu Cord +1
We address the issue of speeding up the training of convolutional networks. Here we study a distributed method adapted to stochastic gradient descent (SGD). The parallel optimizati…
Maxmin convolutional neural networks for image classification
Michael Blot, Matthieu Cord, Nicolas Thome
Convolutional neural networks (CNN) are widely used in computer vision, especially in image classification. However, the way in which information and invariance properties are enco…
Master's Thesis : Deep Learning for Visual Recognition
Rémi Cadène, Nicolas Thome, Matthieu Cord
The goal of our research is to develop methods advancing automatic visual recognition. In order to predict the unique or multiple labels associated to an image, we study different…