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Publications associées (30)

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Machine-Learning Based Monitoring of Cognitive Workload in Rescue Missions with Drones

David Atienza Alonso, Dario Floreano, Ricardo Andres Chavarriaga Lozano, Adriana Arza Valdes, Fabio Isidoro Tiberio Dell'Agnola, Ping-Keng Jao

In search and rescue missions, drone operations are challenging and cognitively demanding. High levels of cognitive workload can affect rescuers’ performance, leading to failure with catastrophic outcomes. To face this problem, we propose a machine learnin ...

2022

ExG Signal Feature Selection Using Hyperdimensional Computing Encoding

David Atienza Alonso, Tomas Teijeiro Campo, Una Pale

Wearable IoT devices and novel continuous monitoring algorithms are essential components of the healthcare transition from reactive interventions focused on symptom treatment to more proactive prevention, from one-size-fits-all to personalized medicine, an ...

IEEE2022

Measurement in the Age of Information

Marilyne Andersen, Forrest Simon Webler

Information is the resolution of uncertainty and manifests itself as patterns. Although complex, most observable phenomena are not random and instead are associated with deterministic, chaotic systems. The underlying patterns and symmetries expressed from ...

2022

Hubbard U through polaronic defect states

Alfredo Pasquarello, Stefano Falletta

Since the preliminary work of Anisimov and co-workers, the Hubbard corrected DFT+U functional has been used for predicting properties of correlated materials by applying on-site effective Coulomb interactions to specific orbitals. However, the determinatio ...

NATURE PORTFOLIO2022

Indexing Protected Deep Face Templates by Frequent Binary Patterns

Sébastien Marcel, Hatef Otroshi Shahreza

In this work, we present a simple biometric indexing scheme which is binning and retrieving cancelable deep face templates based on frequent binary patterns. The simplicity of the proposed approach makes it applicable to unprotected as well as protected, i ...

IEEE2022

SporTran: A code to estimate transport coefficients from the cepstral analysis of (multivariate) current time series

Loris Ercole

SporTran is a Python utility designed to estimate generic transport coefficients in extended systems, based on the Green-Kubo theory of linear response and the recently introduced cepstral analysis of the current time series generated by molecular dynamics ...

ELSEVIER2022

Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition

Tao Lin

In wearable-based human activity recognition (HAR) research, one of the major challenges is the large intra-class variability problem. The collected activity signal is often, if not always, coupled with noises or bias caused by personal, environmental, or ...

ASSOC COMPUTING MACHINERY2022

Continual Test-Time Domain Adaptation

Olga Fink

Test-time domain adaptation aims to adapt a source pretrained model to a target domain without using any source data. Existing works mainly consider the case where the target domain is static. However, real-world machine perception systems are running in n ...

IEEE COMPUTER SOC2022

Predicting in Uncertain Environments: Methods for Robust Machine Learning

Paul Thierry Yves Rolland

One of the main goal of Artificial Intelligence is to develop models capable of providing valuable predictions in real-world environments. In particular, Machine Learning (ML) seeks to design such models by learning from examples coming from this same envi ...

EPFL2022

Feature distribution learning by passive exposure

David Pascucci, Gizay Ceylan

Humans can rapidly estimate the statistical properties of groups of stimuli, including their average and variability. But recent studies of so-called Feature Distribution Learning (FDL) have shown that observers can quickly learn even more complex aspects ...

2022