Publications associées à Energy-Efficient Continuous Activity Recognition on Mobile Phones: An Activity-Adaptive Approach

Spatially-Variant CNN-Based Point Spread Function Estimation for Blind Deconvolution and Depth Estimation in Optical Microscopy

Michael Stefan Daniel Liebling, Adrian Shajkofci

Optical microscopy is an essential tool in biology and medicine. Imaging thin, yet non-flat objects in a single shot (without relying on more sophisticated sectioning setups) remains challenging as the shallow depth of field that comes with high-resolution ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Wearable 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 ...

EPFL2020

Discrete Time Analysis of Phase Detector Timing Nonidealities in Type-I Sub-Sampling PLL

Yusuf Leblebici, Duygu Kostak

The analysis of the effect of sub-sampling phase detector (SSPD) timing nonidealities on Type-I sub-sampling phase-locked loop (SSPLL) is presented. The nonidealities considered are the delay between the complementary sampling clocks and the propagation de ...

IEEE2020

The diagnostic potential of multimodal neuroimaging measures in Parkinson's disease and atypical parkinsonism

Chang-Hyun Park

Introduction For the diagnosis of Parkinson's disease (PD) and atypical parkinsonism (AP) using neuroimaging, structural measures have been largely employed since structural abnormalities are most noticeable in the diseases. Functional abnormalities have b ...

2020

ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification

Mahsa Shoaran, Bingzhao Zhu

Classifiers that can be implemented on chip with minimal computational and memory resources are essential for edge computing in emerging applications such as medical and IoT devices. This paper introduces a machine learning model based on oblique decision ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Renewable energy storage via CO2 and H-2 conversion to methane and methanol: Assessment for small scale applications

Andreas Züttel, Robin Tobias Andreas Mutschler, Emanuele Moioli

This study analyses the power to methane - and to methanol processes in the view of their efficiency in energy storage. A systematic investigation of the differences on the two production systems is performed. The energy storage potential of CO2 to methano ...

PERGAMON-ELSEVIER SCIENCE LTD2019

HideMyApp: Hiding the Presence of Sensitive Apps on Android

Jean-Pierre Hubaux, Kévin Clément Huguenin, Thi Van Anh Pham, Italo Ivan Dacosta Petrocelli, John Stephan, Eleonora Losiouk

Millions of users rely on mobile health (mHealth) apps to manage their wellness and medical conditions. Although the popularity of such apps continues to grow, several privacy and security challenges can hinder their potential. In particular, the simple fa ...

Proceedings of the 28th USENIX Security Symposium2019

HideMyApp : Hiding the Presence of Sensitive Apps on Android

Jean-Pierre Hubaux, Kévin Clément Huguenin, Thi Van Anh Pham, Italo Ivan Dacosta Petrocelli, John Stephan, Eleonora Losiouk

Millions of users rely on mobile health (mHealth) apps to manage their wellness and medical conditions. Although the popularity of such apps continues to grow, several privacy and security challenges can hinder their potential. In particular, the simple fa ...

2019

HideMyApp : Hiding the Presence of Sensitive Apps on Android

Jean-Pierre Hubaux, Kévin Clément Huguenin, Italo Ivan Dacosta Petrocelli, John Stephan, Eleonora Losiouk

Millions of users rely on mobile health (mHealth) apps to manage their wellness and medical conditions. Although the popularity of such apps continues to grow, several privacy and security challenges can hinder their potential. In particular, the simple fa ...

USENIX ASSOC2019