5 papers
Learning Sparse Filters in Deep Convolutional Neural Networks with a l1/l2 Pseudo-Norm
Anthony Berthelier, Yongzhe Yan, Thierry Chateau +3
While deep neural networks (DNNs) have proven to be efficient for numerous tasks, they come at a high memory and computation cost, thus making them impractical on resource-limited…
Machine learning of committor functions for predicting high impact climate events
Dario Lucente, Stefan Duffner, Corentin Herbert +2
There is a growing interest in the climate community to improve the prediction of high impact climate events, for instance ENSO (El-Ni{ñ}o-Southern Oscillation) or extreme events,…
Facial Landmark Correlation Analysis
Yongzhe Yan, Stefan Duffner, Priyanka Phutane +4
We present a facial landmark position correlation analysis as well as its applications. Although numerous facial landmark detection methods have been presented in the literature, f…
2D Wasserstein Loss for Robust Facial Landmark Detection
Yongzhe Yan, Stefan Duffner, Priyanka Phutane +4
The recent performance of facial landmark detection has been significantly improved by using deep Convolutional Neural Networks (CNNs), especially the Heatmap Regression Models (HR…
Routine Modeling with Time Series Metric Learning
Paul Compagnon, Grégoire Lefebvre, Stefan Duffner +1
Traditionally, the automatic recognition of human activities is performed with supervised learning algorithms on limited sets of specific activities. This work proposes to recogniz…