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Publications associées (32)
Humidity Sensors for High Energy Physics Applications: A Review
Sandro Carrara, Andromachi Tsirou, Amar Kapic
Modern silicon-based detectors for high-energy physics operate in an experimental environment with sub-zero temperatures. At those temperatures, even low traces of humidity will produce vapor condensation with damages to the detectors. Monitoring relative ...
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020Wearable and Self-Aware Machine Learning System for Online Cognitive Workload Monitoring and Drone Control
Fabio Isidoro Tiberio Dell'Agnola
The use of robots in search and rescue is gaining particular interest, but singular skills are required to ensure efficient deployments in real missions.
To face this problem, there is a need to develop more intuitive control interfaces.
Moreover, to ensur ...
EPFL2020Contextual semantic interpretability
Devis Tuia, Sylvain Lobry, Nicolas Courty
Convolutional neural networks (CNN) are known to learn an image representation that captures concepts relevant to the task, but do so in an implicit way that hampers model interpretability. However, one could argue that such a representation is hidden in t ...
LNCS2020Recent experiments with the European 1MW, 170GHz industrial CW and short-pulse gyrotrons for ITER
Stefano Alberti, Minh Quang Tran, Jean-Philippe Hogge, Christian Schlatter, Jérémy Genoud, Francisco Sanchez, Ioannis Pagonakis, Konstantinos Avramidis
The European Gyrotron Consortium (EGYC) is developing the European 1 MW, 170 GHz Continuous Wave (CW) industrial prototype gyrotron for ITER in cooperation with Thales Electron Devices (TED) and Fusion for Energy (F4E). This conventional, hollow-cavity gyr ...
ELSEVIER SCIENCE SA2019Lean synthesis and application to lower-limb exoskeletons
Mobility impairments are the most prevalent of all disabilities, affecting the life of nearly one in 20 individuals in developed countries. In the most severe cases, they can have dramatic consequences for the social, mental and physical well-being of thos ...
EPFL2019Deep Neural Networks for seeing through multimode fibers
Demetri Psaltis, Christophe Moser, Navid Borhani, Eirini Kakkava
Image delivery through multimode fibers (MMFs) suffers from modal scrambling which results in a speckle pattern at the fiber output. In this work, we use Deep Neural Networks (DNNs) for recovery and/or classification of the input image from the intensity-o ...
SPIE-INT SOC OPTICAL ENGINEERING2019