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Related publications (25)

Computation of sensitivity coefficients in fixed source simulations with SERPENT2

Andreas Pautz, Mathieu Hursin

Within the scope of the implementation of a nuclear data pipeline aiming at producing the best possible evaluated nuclear data files, a major point is the production of relevant sensitivity coefficients when including integral benchmark information. Thanks ...

Elsevier Science Sa2024

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Michele Bianco, Tianyue Chen

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Oxford Univ Press2024

Resource-Efficient Continual Learning for Personalized Online Seizure Detection

David Atienza Alonso, Giovanni Ansaloni, Flavio Ponzina, José Angel Miranda Calero, Jonathan Dan, Amirhossein Shahbazinia

Epilepsy, a major neurological disease, requires careful diagnosis and treatment. However, the detection of epileptic seizures remains a significant challenge. Current clinical practice relies on expert analysis of EEG signals, a process that is time-consu ...

IEEE2024

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Seyedbehzad Bozorgtabar

Informative sample selection in an active learning (AL) setting helps a machine learning system attain optimum performance with minimum labeled samples, thus reducing annotation costs and boosting performance of computer-aided diagnosis systems in the pres ...

Elsevier2024

A Multicenter Longitudinal MRI Study Assessing LeMan-PV Software Accuracy in the Detection of White Matter Lesions in Multiple Sclerosis Patients

Tobias Kober, Meritxell Bach Cuadra, Cristina Granziera, Bénédicte Marie Maréchal, Muhamed Barakovic, Ricardo Alberto Corredor Jerez, Lester Melie Garcia

BackgroundDetecting new and enlarged lesions in multiple sclerosis (MS) patients is needed to determine their disease activity. LeMan-PV is a software embedded in the scanner reconstruction system of one vendor, which automatically assesses new and enlarge ...

WILEY2023

Machine learning-derived gut microbiome signature predicts fatty liver disease in the presence of insulin resistance

Johan Auwerx, Dongryeol Ryu

A simple predictive biomarker for fatty liver disease is required for individuals with insulin resistance. Here, we developed a supervised machine learning-based classifier for fatty liver disease using fecal 16S rDNA sequencing data. Based on the Kangbuk ...

Nature Portfolio2022

Removing Algorithmic Discrimination (With Minimal Individual Error)

Rachid Guerraoui, El Mahdi El Mhamdi, Alexandre David Olivier Maurer, Le Nguyen Hoang

We address for the first time the problem of correcting group discriminations within a score function, while minimizing the individual error. Each group is described by a probability density function on the set of profiles. We first solve the problem analy ...

2022

Kernel Density Estimation of Electromyographic Signals and Ensemble Learning for Highly Accurate Classification of a Large Set of Hand/Wrist Motions

Parviz Ghaderi

The performance of myoelectric control highly depends on the features extracted from surface electromyographic (sEMG) signals. We propose three new sEMG features based on the kernel density estimation. The trimmed mean of density (TMD), the entropy of dens ...

FRONTIERS MEDIA SA2022

Fast screening of covariates in population models empowered by machine learning

Jan Sickmann Hesthaven

One of the objectives of Pharmacometry (PMX) population modeling is the identification of significant and clinically relevant relationships between parameters and covariates. Here, we demonstrate how this complex selection task could benefit from supervise ...

2021

Wearable and Continuous Prediction of Passage of Time Perception for Monitoring Mental Health

David Atienza Alonso, Lara Orlandic, Adriana Arza Valdes

A person’s passage of time perception (POTP) is strongly linked to their mental state and stress response, and can therefore provide an easily quantifiable means of continuous mental health monitoring. In this work, we develop a custom experiment and Machi ...

2021

Pedestrian intention prediction: A convolutional bottom-up multi-task approach

Alexandre Massoud Alahi, Taylor Ferdinand Mordan

The ability to predict pedestrian behaviour is crucial for road safety, traffic management systems, Advanced Driver Assistance Systems (ADAS), and more broadly autonomous vehicles. We present a vision-based system that simultaneously locates where pedestri ...

2021

Identification of blowing snow particles in images from a Multi-Angle Snowflake Camera

Alexis Berne, Christophe Praz, Mathieu Oscar Schaer

A new method to automatically discriminate between hydrometeors and blowing snow particles on MultiAngle Snowflake Camera (MASC) images is introduced. The method uses four selected descriptors related to the image frequency, the number of particles detecte ...

2020

Evaluating salient object detection in natural images with multiple objects having multi-level saliency

Sabine Süsstrunk, Gökhan Yildirim

Salient object detection is evaluated using binary ground truth (GT) with the labels being salient object class and background. In this study, the authors corroborate based on three subjective experiments on a novel image dataset that objects in natural im ...

2020

Benchmark for Human-to-Robot Handovers of Unseen Containers with Unknown Filling

Pascal Frossard, Aude Billard, Andrea Cavallaro, Apostolos Modas, Nuno Ricardo Ferreira Duarte, Konstantinos Chatzilygeroudis

The real-time estimation through vision of the physical properties of objects manipulated by humans is important to inform the control of robots for performing accurate and safe grasps of objects handed over by humans. However, estimating the 3D pose and d ...

2020

Monitoring of Cardiovascular and Neurological Diseases Using Wearable Devices

Dionisije Sopic

In this thesis, I focus on monitoring of patients suffering from cardiovascular and neurological diseases through the use of wearable devices. The main diseases considered in this thesis are atrial fibrillation (AF), myocardial infarction (MI), and epileps ...

EPFL2020

BookTubing Across Regions: Examining Differences based on Nonverbal and Verbal Cues

Daniel Gatica-Perez, Dinesh Babu Jayagopi

BookTubers are a rapidly growing community in YouTube who shares content related to books. Previous literature has addressed problems related to automatically analyzing opinions and mood of video logs (vlogs) as a generic category in YouTube. Unfortunately ...

ASSOC COMPUTING MACHINERY2019

A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience

Christian O'Reilly, Elisabetta Iavarone

The curation of neuroscience entities is crucial to ongoing efforts in neuroinformatics and computational neuroscience, such as those being deployed in the context of continuing large-scale brain modelling projects. However, manually sifting through thousa ...

Springer2019

Analysis of EEG Correlates of Perceived Difficulty in Dynamically Changing Flying Tasks

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Ping-Keng Jao

Real-time workload estimation can be an important tool to improve human-machine interaction. Despite multiple efforts in this sense, most studies focused on tasks designed to have extreme conditions of workload (high vs low), and these levels remain rather ...

IEEE2018

Action Units and Their Cross-Correlations for Prediction of Cognitive Load during Driving

Jean-Philippe Thiran, Anil Yuce, Hua Gao, Gabriel Louis Cuendet

Driving requires the constant coordination of many body systems and full attention of the person. Cognitive distraction (subsidiary mental load) of the driver is an important factor that decreases attention and responsiveness, which may result in human err ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Improving activity recognition using a wearable barometric pressure sensor in mobility-impaired stroke patients

Kamiar Aminian, Anisoara Ionescu, Arash Arami, Fabien Massé

Background Stroke survivors often suffer from mobility deficits. Current clinical evaluation methods, including questionnaires and motor function tests, cannot provide an objective measure of the patients’ mobility in daily life. Physical activity performa ...

BioMed Central2015