In recent years, deep architectures have been used for transfer learning with state-of-the-art
performance in many datasets. The properties of their features remain, however, largely …

The immense diffusion of smart mobile devices increase the usage of WiFi as a state-of-the-
art wireless communication standard dramatically, and it also renders fingerprinting method …

In many machine learning and pattern recognition tasks, there is always a need for
appropriate metric functions to measure pairwise distance or similarity between data, where …

The objective of this document is to introduce the principle of Autonomous PErceptual
System (APES) as an object of study. The functionalities of artificial perception, in particular …

In recent years, Deep Learning techniques have swept the state-of-the-art of many
applications of Machine Learning, becoming the new standard approach for them. The …

Various research efforts have been undertaken to solve the problem of trajectory privacy
preservation in the Internet of Things (IoT) of resource-constrained mobile devices. Most …

" No two leaves are exactly alike."—Gottfried Wilhelm Leibniz This dictum of Leibniz reveals
that differences are ubiquitous in this world. Besides, we can also realize another fact that he …

This paper introduces a novel similarity learning frame-work. Working with inequality
constraints involving quadruplets of images, our approach aims at efficiently modeling …

Dans cette thèse nous étudions différentes questions relatives à la mise en pratique de
modèles d'apprentissage profond. En effet malgré les avancées prometteuses de ces …