Automatic casting applications aim is to accurately recognise facial regions that correspond to a same actor appearing in a movie to produce described video. This project will focus on the tasks of re-identify the face of each principal actors when they appear in different scenes of a movie. This is a challenging task because although […]

This project aims at creating a robust, efficient and reliable tool for Named Entities Recognition (NER) from vast amounts of textual data related to the customer service. Named entities recognition, a subtask of information extraction, seeks to locate and classify elements in text into pre-defined categories such as the names of persons, organizations, locations, expressions […]

Le projet consiste à bâtir un outil permettant d’évaluer les économies que les clients peuvent espérer en mettant en place le procédé et le logiciel proposé par Merinio. Le logiciel est un outil permettant de faire la gestion de la main d’œuvre de façon plus efficace en automatisant des tâches, en éliminant des tâches répétitives […]

Head-mounted displays (HMDs) allow a convenient delivery of visualized data to the user. HMDs in the form of glasses and goggles (otherwise known as smart glasses and goggles), such as Vuzix Blade and Epson Moverio [1-3], have been introduced but the public acceptance of these devices have been rather lackluster. Part of the sluggish acceptance […]

Video analytics is an active fields of research, where state-of-the-art systems rely on a variety of computer vision and machine learning techniques for accurate modeling and recognition from large-scale video datasets. Person re-identification is a key problem found in numerous application areas, e.g., video surveillance, summarization, and sports analysis, and seeks to match people across […]

Video analytics is an active fields of research, where state-of-the-art systems rely on a variety of computer vision and machine learning techniques for accurate modeling and recognition from large-scale video datasets. Person re-identification is a key problem found in numerous application areas, e.g., video surveillance, summarization, and sports analysis, and seeks to match people across […]

Image denoising is a fundamental process in most of computer vision systems, imaging systems, and photography productions. Recently, with the power of deep neural networks, image denoising has been pushed towards new boundaries. However, neural network image denoisers are constrained by the accuracy of the noise model used to train them. Training on a poor […]

Model-free Reinforcement Learning (RL) has recently demonstrated its great potential in solving difficult intelligent tasks. However, developing a successful RL model requires an extensive model tuning and tremendous training samples. Theoretical analysis of these RL methods, more specifically policy optimization methods, only stay in a simple setting where the learning happens in the policy space. […]

L’optimisation combinatoire occupe une place prépondérante dans notre société actuelle. Que ce soit la logistique, le transport ou la gestion financière, tous ses domaines se retrouvent confrontés à des problèmes pour lesquels on recherche la meilleure solution. Cependant, un grand nombre de problèmes très complexes reste encore hors de portée des méthodes d’optimisation actuelles. C’est […]

Machine learning approaches are transforming fields such as finance, healthcare, electronic commerce, social networks, and natural disaster forecasting. We propose collaborative research that develops novel methods and applications of machine learning techniques for event prediction, modeling relations between entities, and inference techniques that can impact these domains. In the context of event prediction, we will […]

The recent advances in machine learning based on deep neural networks, coupled with the availability of phenomenal storage capacity, are transforming the industrial landscape. However, these novel machine learning approaches are known to be data hungry, as they need to tune a huge number of parameters in order to perform well. As more and more […]

Compilers are large software projects consisting of many separate but common components like code generators, garbage collectors, and runtime diagnostic tools, to name but a few. Historically compiler developers have had to write each of these components from scratch. The Eclipse OMR project was created to provide generic components for use in new compilers and […]