activity
20232025
most citedA Novel Transformer-Based Self-Supervised Learning Method to Enhance Photoplethysmogram Signal Artifact Detection

4 citations · 12 across the 5 of their papers we have counts for

collaborators

5 papers

astro-ph.IM2025

Euclid preparation: The NISP spectroscopy channel, on ground performance and calibration

Euclid Collaboration, W. Gillard, T. Maciaszek +356

ESA's Euclid cosmology mission relies on the very sensitive and accurately calibrated spectroscopy channel of the Near-Infrared Spectrometer and Photometer (NISP). With three opera…

eess.SP2024★ 1 cited

Transformer Meets Gated Residual Networks To Enhance Photoplethysmogram Artifact Detection Informed by Mutual Information Neural Estimation

Thanh-Dung Le, Clara Macabiau, Kévin Albert +3

This study delves into the effectiveness of various learning methods in improving Transformer models, focusing particularly on the Gated Residual Network Transformer (GRN-Transform…

cs.LG2024★ 4 cited

A Novel Transformer-Based Self-Supervised Learning Method to Enhance Photoplethysmogram Signal Artifact Detection

Thanh-Dung Le, Clara Macabiau, Kévin Albert +2

Recent research at CHU Sainte Justine's Pediatric Critical Care Unit (PICU) has revealed that traditional machine learning methods, such as semi-supervised label propagation and K-…

cs.LG2023★ 4 cited

Label Propagation Techniques for Artifact Detection in Imbalanced Classes using Photoplethysmogram Signals

Clara Macabiau, Thanh-Dung Le, Kevin Albert +3

This study aimed to investigate the application of label propagation techniques to propagate labels among photoplethysmogram (PPG) signals, particularly in imbalanced class scenari…

eess.SP2023★ 3 cited

GRN-Transformer: Enhancing Motion Artifact Detection in PICU Photoplethysmogram Signals

Thanh-Dung Le, Clara Macabiau, Kévin Albert +2

Photoplethysmogram (PPG) signals, optical measurements of pulsatile blood flow used continuously in intensive care monitoring, are frequently contaminated by motion, low perfusion,…