The main goal of this work is to implement and provide a theoretical description of different schemes of Physical-layer Network Coding. Using a basic setup as starting point, the manuscript presents the construction and performance of different systems of communications with increasing complexity. The text is structured in different sections: first, an introduction to Physical-layer Network Coding and Lattice Network Codes is delivered. Next, the mathematical tools required to understand the system of Compute and Forward (C&F) are presented. Further, a first basic scheme is analysed and...

The main aim of the text is to give a review of fast kernel expansions, FOURIER features and rapid numerical code in statistical learning. For this purpose we introduce a library for approximating kernel expansions, which enables the use of kernel methods in datasets with a large number of samples. It is well-known that kernel methods as originally proposed are computational costly for big data, we explain here the theory needed to enable the use of non-linear features in log-linear time. This approximation is based on FOURIER features by the use of the Walsh Hadamard. A SIMD implementation...

Generative Adversarial Networks (GANs) have had tremendous applications in Computer Vision. Yet, in the context of space science and planetary exploration the door is open for major advances. We introduce tools to handle planetary data from the mission Chang'E-4 and present a framework for Neural Style Transfer using Cycle-consistency from rendered images. We also introduce a new real-time pipeline for Simultaneous Localization and Mapping (SLAM) and Visual Inertial Odometry (VIO) in the context of planetary rovers. We leverage prior information of the location of the lander to propose an...

Generative Adversarial Networks (GANs) haben in der Computer Vision enorme Anwendungen gefunden. Doch im Kontext der Weltraumwissenschaft und Planetenerkundung steht die Tür für große Fortschritte offen. Wir stellen Tools zum Umgang mit Planetendaten der Mission Chang'E-4 vor und präsentieren ein Framework für die Neural Style Transfer unter Verwendung von Cycle-Consistency aus gerenderten Bildern. Wir führen auch eine neue Echtzeit-Pipeline für Simultaneous Localization and Mapping (SLAM) und Visual Inertial Odometry (VIO) im Zusammenhang mit planetaren Rovern ein. Wir nutzen...

Les réseaux antagonistes génératifs (GAN) ont eu d'énormes applications dans la vision par ordinateur. Pourtant, dans le contexte des sciences spatiales et de l'exploration planétaire, la porte est ouverte à des avancées majeures. Nous introduisons des outils pour gérer les données planétaires de la mission Chang'E-4 et présentons un cadre pour le transfert de style neuronal utilisant la cohérence cyclique à partir d'images rendues. Nous introduisons également un nouveau pipeline en temps réel pour la localisation et la cartographie simultanées (SLAM) et l'odométrie...