Research Explorer

Uw browser ondersteunt geen JavaScript of JavaScript is niet ingeschakeld. Zonder JavaScript kan sommige functionaliteit van deze webapplicatie uitgeschakeld zijn of foutmeldingen veroorzaken. Raadpleeg om JavaScript in te schakelen de handleiding van uw browser of contacteer uw systeembeheerder.

Onderzoeker

Lorin Werthen-Brabants

Prijzen & Erkenningen

18 Resultaten

2025

Deep learning-based event counting for apnea-hypopnea index estimation using recursive spiking neural networks

Lorin Werthen-BrabantsYolanda Castillo-EscarioWillemijn GroenendaalRaimon JaneTom DhaeneDirk Deschrijver

A1 Artikel in een tijdschrift in IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Leveraging hand-crafted radiomics on multicenter FLAIR MRI for predicting disability progression in people with multiple sclerosis

Hamza KhanHenry C WoodruffDiana L. GiraldoLorin Werthen-BrabantsShruti Atul MaliSina AmirrajabEdward De BrouwerVeronica PopescuBart Van WijmeerschOliver Gerlach et al.

The role of trustworthy and reliable AI for multiple sclerosis

Lorin Werthen-BrabantsTom DhaeneDirk Deschrijver

A2 Artikel in een tijdschrift in FRONTIERS IN DIGITAL HEALTH

2024

Data-driven surrogate modeling for the flammability reduction system

Arash HeidariLorin Werthen-BrabantsTom DhaeneIvo CouckuytC. OnurP. Van GilsI. Jojic

Machine-learning-based prediction of disability progression in multiple sclerosis : an observational, international, multi-center study

Edward De BrouwerThijs BeckerLorin Werthen-BrabantsPieter DewulfDimitrios IliadisCathérine DekeyserGuy LaureysBart Van WijmeerschVeronica PopescuTom Dhaene et al.

A2 Artikel in een tijdschrift in PLOS DIGITAL HEALTH

Optimized data transmission for radar-based edge-cloud human activity recognition via quantization

Victor TuytteArash HeidariLorin Werthen-BrabantsTom DhaeneIvo Couckuyt

Optimizing memory footprint for radar-based human activity recognition on resource-constrained devices

Arash HeidariLorin Werthen-BrabantsTom DhaeneIvo Couckuyt

Towards trustworthy neural networks for certification by analysis : fuel tank flammability reduction system

P. Van GilsC. OnurI. JojicArash HeidariSebastian Rojas GonzalezLorin Werthen-BrabantsIvo Couckuyt

2023

Open-set patient activity recognition with radar sensors and deep learning

Geethika BhavanasiLorin Werthen-BrabantsTom DhaeneIvo Couckuyt

A1 Artikel in een tijdschrift in IEEE GEOSCIENCE AND REMOTE SENSING LETTERS

Quantifying uncertainty and improving reliability of time-series based deep learning models

Lorin Werthen-BrabantsDirk DeschrijverTom Dhaene

Reliable assessment of uncertainty for appliance recognition in NILM using conformal prediction

Lorin Werthen-BrabantsTom DhaeneDirk Deschrijver

A1 Artikel in een tijdschrift in ELECTRONICS LETTERS

2022

Convolutional neural networks for apnea detection from smartphone audio signals : effect of window size

Yolanda Castillo-EscarioLorin Werthen-BrabantsWillemijn GroenendaalDirk DeschrijverRaimon Jane

Machine-learning-based prediction of disability progression in multiple sclerosis : an observational, international, multi-center study

Edward De BrouwerThijs BeckerLorin Werthen-BrabantsPieter DewulfDimitrios IliadisCathérine DekeyserGuy LaureysBart Van WijmeerschVeronica PopescuTom Dhaene et al.

Patient activity recognition using radar sensors and machine learning

Geethika BhavanasiLorin Werthen-BrabantsTom DhaeneIvo Couckuyt

A1 Artikel in een tijdschrift in NEURAL COMPUTING & APPLICATIONS

Quantifying uncertainty in real time with split BiRNN for radar human activity recognition

Lorin Werthen-BrabantsGeethika BhavanasiIvo CouckuytTom DhaeneDirk Deschrijver

Split BiRNN for real-time activity recognition using radar and deep learning

Lorin Werthen-BrabantsGeethika BhavanasiIvo CouckuytTom DhaeneDirk Deschrijver

A1 Artikel in een tijdschrift in SCIENTIFIC REPORTS

Tailoring radar-based patient monitoring models to real-life needs using utility maximization

Louis Vincent-De SlooverLorin Werthen-BrabantsGeethika BhavanasiTom DhaeneIvo Couckuyt

Uncertainty quantification for appliance recognition in non-intrusive load monitoring using Bayesian deep learning

Lorin Werthen-BrabantsTom DhaeneDirk Deschrijver

A1 Artikel in een tijdschrift in ENERGY AND BUILDINGS