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Researcher
Lorin Werthen-Brabants
Profile
Projects
Publications
Activities
Awards & Distinctions
10
Results
2023
Open-set patient activity recognition with radar sensors and deep learning
Geethika Bhavanasi
Lorin Werthen-Brabants
Tom Dhaene
Ivo Couckuyt
A1
Journal Article
in
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
2023
Quantifying Uncertainty and Improving Reliability of Time-Series Based Deep Learning Models
Lorin Werthen-Brabants
Dirk Deschrijver
Tom Dhaene
Dissertation
2023
Reliable assessment of uncertainty for appliance recognition in NILM using conformal prediction
Lorin Werthen-Brabants
Tom Dhaene
Dirk Deschrijver
U
Journal Article
in
ELECTRONICS LETTERS
2023
2022
Convolutional neural networks for apnea detection from smartphone audio signals : effect of window size
Yolanda Castillo-Escario
Lorin Werthen-Brabants
Willemijn Groenendaal
Dirk Deschrijver
Raimon Jane
C1
Conference
2022
Machine-learning-based prediction of disability progression in multiple sclerosis : an observational, international, multi-center study
Edward De Brouwer
Thijs Becker
Lorin Werthen-Brabants
Pieter Dewulf
Dimitrios Iliadis
Cathérine Dekeyser
Guy Laureys
Bart Van Wijmeersch
Veronica Popescu
Tom Dhaene
et al.
Preprint
2022
Patient activity recognition using radar sensors and machine learning
Geethika Bhavanasi
Lorin Werthen-Brabants
Tom Dhaene
Ivo Couckuyt
A1
Journal Article
in
NEURAL COMPUTING & APPLICATIONS
2022
Quantifying uncertainty in real time with split BiRNN for radar human activity recognition
Lorin Werthen-Brabants
Geethika Bhavanasi
Ivo Couckuyt
Tom Dhaene
Dirk Deschrijver
P1
Conference
2022
Split BiRNN for real-time activity recognition using radar and deep learning
Lorin Werthen-Brabants
Geethika Bhavanasi
Ivo Couckuyt
Tom Dhaene
Dirk Deschrijver
A1
Journal Article
in
SCIENTIFIC REPORTS
2022
Tailoring radar-based patient monitoring models to real-life needs using utility maximization
Louis Vincent-De Sloover
Lorin Werthen-Brabants
Geethika Bhavanasi
Tom Dhaene
Ivo Couckuyt
P1
Conference
2022
Uncertainty quantification for appliance recognition in non-intrusive load monitoring using Bayesian deep learning
Lorin Werthen-Brabants
Tom Dhaene
Dirk Deschrijver
A1
Journal Article
in
ENERGY AND BUILDINGS
2022