L’objectif de cette thèse est d’apporter différentes contributions méthodologiques en bioacoustique pour l’étude de la faune. En effet, la bioacoustique est une science récente, pluridisciplinaire et très efficace pour étudier et classifier un écosystème. Beaucoup d’études ont mis au point des procédés acoustiques pour étudier la faune à des échell...
Machine Learning has received a lot of attention during the last two decades both from industry for data-driven decision problems and from the scientific community in general. This recent attention is certainly due to its ability to efficiently solve a wide class of high-dimensional problems with fast and easy- to-implement algorithms. What is the ...
Les exploitants nucléaires produisent des comptes rendus d'analyse de tout événement significatif. Un démonstrateur mettant en oeuvre des algorithmes de traitement automatique du langage naturel a été testé. Les résultats sont prometteurs, mais questionnent sur la place qu'ils peuvent prendre au regard des transitions qui s'opèrent dans les pratiqu...
The Milky Way (MW) large-scale structure is still not under very strong observational constraints. Studying the morphology of other galaxies is straightforward but the observation of our home galaxy is made difficult by our internal viewpoint. Stellar confusion and screening by interstellar matter are strong observational limitations to assess the ...
The deep learning approach to AI has taken upon the whole society thanks to the use of Graphical Computing Units (GPUs). Going beyond the capability of the GPUs for deep neural network training is the core motivation of this thesis. One possible approach is neuromorphic computing, which consists in rethinking the computer from scratch by mimicking ...
L’apprentissage statistique fournit un cadre aux problèmes de prédiction, où l’on cherche à prédire des quantités inconnues à partir d’exemples.La première partie de cette thèse porte sur les méthodes de Forêts aléatoires, une famille d'algorithmes couramment utilisés en pratique, mais dont l'étude théorique s'avère délicate. Notre principale contr...
With the evolution of technology, the use of smart Internet-of-Things (IoT) devices, sensors, and social networks result in an overwhelming volume of IoT data streams, generated daily from several applications, that can be transformed into valuable information through machine learning tasks. In practice, multiple critical issues arise in order to e...
Artificial Intelligence (AI) and Human-Computer Interactions (HCIs) are two research fields with relatively few common work. HCI specialists usually design the way we interact with devices directly from observations and measures of human feedback, manually optimizing the user interface to better fit users’ expectations. This process is hard to opti...
International audience
For nearly two decades, patrolling has received significant attention from the multiagent community. Multiagent patrolling (MAP) consists in modelling a patrol task to optimise as a multiagent system. The problem of optimising a patrol task is to distribute the most efficiently agents over the area to patrol in space and time, which constitutes a d...
