Classement automatique

Science formelle
Statistique
Analyse des données
Classement automatique

Publications associées (29)

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A platform for experimental precision medicine: The extended BXD mouse family

Johan Auwerx, Evan Graehl Williams

The challenge of precision medicine is to model complex interactions among DNA variants, phenotypes, development, environments, and treatments. We address this challenge by expanding the BXD family of mice to 140 fully isogenic strains, creating a uniquely ...

CELL PRESS2021

SiML: Sieved Maximum Likelihood for Array Signal Processing

Paul Hurley, Matthieu Martin Jean-André Simeoni

Stochastic Maximum Likelihood (SML) is a popular direction of arrival (DOA) estimation technique in array signal processing. It is a parametric method that jointly estimates signal and instrument noise by maximum likelihood, achieving excellent statistical ...

2021

Interpreting deep learning models for epileptic seizure detection on EEG signals

David Atienza Alonso, Marina Zapater Sancho, Tomas Teijeiro Campo, Valentin Alexandre Guy Gabeff, Leila Cammoun

While Deep Learning (DL) is often considered the state-of-the art for Artificial Intelligence-based medical decision support, it remains sparsely implemented in clinical practice and poorly trusted by clinicians due to insufficient interpretability of neur ...

2021

Model-Class Selection Using Clustering and Classification for Structural Identification and Prediction

Ian Smith, Sai Ganesh Sarvotham Pai, Masoud Sanayei

Structural identification using physics-based models and subsequent prediction have much potential to enhance civil infrastructure asset-management decision-making. Interpreting monitoring information in the presence of multiple uncertainty sources and sys ...

2021

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

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

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

Constructing a provably adversarially-robust classifier from a high accuracy one

Rüdiger Urbanke, Grzegorz Adam Gluch

Modern machine learning models with very high accuracy have been shown to be vulnerable to small, adversarially chosen perturbations of the input. Given black-box access to a high-accuracy classifier f, we show how to construct a new classifier g that has ...

ADDISON-WESLEY PUBL CO2020

Integrating the Finite Element Method with a Data-Driven Approach for Dam Displacement Prediction

Zhenzhu Meng, Yating Hu, Chenfei Shao

Both numerical simulations and data-driven methods have been applied in dam's displacement modeling. For monitored displacement data-driven methods, the physical mechanism and structural correlations were rarely discussed. In order to take the spatial and ...

2020

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