Publications associées à An inertial sensor-based system for spatio-temporal analysis in classic cross-country skiing diagonal technique

Airborne sensor fusion: Expected accuracy and behavior of a concurrent adjustment

Jan Skaloud, Davide Antonio Cucci, Aurélien Arnaud Brun, Kyriaki Mouzakidou

Tightly-coupled sensor orientation, i.e. the simultaneous processing of temporal (GNSS and raw inertial) and spatial (image and lidar) constraints in a common adjustment, has demonstrated significant improvement in the quality of attitude determination wit ...

2024

VDMNav: Software Architecture for Aerodynamically Constrained Navigation on Small Fixed-Wing Drones

Jan Skaloud, Gabriel François Laupré

Navigation of drones is predominantly based on sensor fusion algorithms. Most of these algorithms make use of some form of Bayesian filtering with a majority employing an Extended Kalman Filter (EKF), wherein inertial measurements are fused with a Global N ...

2024

Leukocyte Count and Coronary Artery Disease Events in People With Human Immunodeficiency Virus: A Longitudinal Study

Jacques Fellay, Christian Axel Wandall Thorball

Leukocyte count is associated with coronary artery disease (CAD) events in the general population. Here we show that leukocytes are independently associated with CAD events in people with HIV in Switzerland, after adjusting for traditional and HIVrelated r ...

OXFORD UNIV PRESS INC2023

Virtual reality intervention alleviates dyspnoea in patients recovering from COVID-19 pneumonia

Olaf Blanke, Bruno Herbelin, Oliver Alan Kannape, Sylvain Cardin, Sophie Jacqueline Andrée Betka, Jemina Fasola, Florian Lance, Aline Schmit

Background Immersive virtual reality (iVR)-based digital therapeutics are gaining clinical attention in the field of pain management. Based on known analogies between pain and dyspnoea, we investigated the effects of visual respiratory feedback on persiste ...

European Respiratory Soc Journals Ltd2023

SoDaCam: Software-defined Cameras via Single-Photon Imaging

Edoardo Charbon, Claudio Bruschini, Andrei Ardelean, Mohit Gupta

Reinterpretable cameras are defined by their post-processing capabilities that exceed traditional imaging. We present "SoDaCam" that provides reinterpretable cameras at the granularity of photons, from photon-cubes acquired by single-photon devices. Photon ...

Ieee Computer Soc2023

Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

Jan Skaloud, Davide Antonio Cucci, Kenneth Joseph Paul

This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs ...

2023

Detecting Anomalies and Obstacles in Road Scenes

Krzysztof Maciej Lis

We address the problem of segmenting anomalies and unusual obstacles in road scenes for the purpose of self-driving safety. The objects in question are not present in the common training sets as it is not feasible to collect and annotate examples for every ...

EPFL2023

Rigidity-Aware Detection for 6D Object Pose Estimation

Mathieu Salzmann, Yinlin Hu, Jingyu Li, Rui Song

Most recent 6D object pose estimation methods first use object detection to obtain 2D bounding boxes before actually regressing the pose. However, the general object detection methods they use are ill-suited to handle cluttered scenes, thus producing poor ...

Ieee Computer Soc2023

How deep convolutional neural networks lose spatial information with training

Matthieu Wyart, Umberto Maria Tomasini, Francesco Cagnetta, Leonardo Petrini

A central question of machine learning is how deep nets manage to learn tasks in high dimensions. An appealing hypothesis is that they achieve this feat by building a representation of the data where information irrelevant to the task is lost. For image da ...

Iop Publishing Ltd2023

Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI

Tobias Kober, Davide Piccini

Purpose: To develop a self-navigated motion compensation strategy for 3D radial MRI that can compensate for continuous head motion by measuring rigid body motion parameters with high temporal resolution from the central k-space acquisition point (self-enco ...

Wiley2023