Tinne De Laet
Title
Cited by
Cited by
Year
Constraint-based task specification and estimation for sensor-based robot systems in the presence of geometric uncertainty
J De Schutter, T De Laet, J Rutgeerts, W Decré, R Smits, E Aertbeliën, ...
The International Journal of Robotics Research 26 (5), 433-455, 2007
2602007
An adaptable system for RGB-D based human body detection and pose estimation
K Buys, C Cagniart, A Baksheev, T De Laet, J De Schutter, C Pantofaru
Journal of visual communication and image representation 25 (1), 39-52, 2014
1142014
Kalman smoothing improves the estimation of joint kinematics and kinetics in marker-based human gait analysis
F De Groote, T De Laet, I Jonkers, J De Schutter
Journal of biomechanics 41 (16), 3390-3398, 2008
1122008
iTASC: a tool for multi-sensor integration in robot manipulation
R Smits, T De Laet, K Claes, H Bruyninckx, J De Schutter
2008 IEEE International Conference on Multisensor Fusion and Integration for …, 2008
592008
A particle filter for hybrid relational domains
D Nitti, T De Laet, L De Raedt
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013
552013
Learning analytics dashboards to support adviser-student dialogue
S Charleer, AV Moere, J Klerkx, K Verbert, T De Laet
IEEE Transactions on Learning Technologies 11 (3), 389-399, 2017
482017
Shape-based online multitarget tracking and detection for targets causing multiple measurements: Variational Bayesian clustering and lossless data association
T De Laet, H Bruyninckx, J De Schutter
IEEE transactions on pattern analysis and machine intelligence 33 (12), 2477 …, 2011
362011
Bayesian time-series models for continuous fault detection and recognition in industrial robotic tasks
E Di Lello, M Klotzbücher, T De Laet, H Bruyninckx
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013
322013
BFL: Bayesian Filtering Library
K Gadeyne, T De Laet
312001
A smoothed GMS friction model suited for gradient-based friction state and parameter estimation
M Boegli, T De Laet, J De Schutter, J Swevers
IEEE/ASME Transactions on mechatronics 19 (5), 1593-1602, 2013
302013
Creating effective learning analytics dashboards: Lessons learnt
S Charleer, J Klerkx, E Duval, T De Laet, K Verbert
European Conference on Technology Enhanced Learning, 42-56, 2016
292016
Probabilistic logic programming for hybrid relational domains
D Nitti, T De Laet, L De Raedt
Machine Learning 103 (3), 407-449, 2016
292016
Literature review and comparison of two statistical methods to evaluate the effect of botulinum toxin treatment on gait in children with cerebral palsy
A Nieuwenhuys, E Papageorgiou, T Pataky, T De Laet, G Molenaers, ...
PloS one 11 (3), e0152697, 2016
292016
Identification of joint patterns during gait in children with cerebral palsy: a Delphi consensus study
A Nieuwenhuys, S Õunpuu, A Van Campenhout, T Theologis, J De Cat, ...
Developmental Medicine & Child Neurology 58 (3), 306-313, 2016
292016
Unified constraint-based task specification for complex sensor-based robot systems
J De Schutter, J Rutgeerts, E Aertbelien, F De Groote, T De Laet, ...
Proceedings of the 2005 IEEE International Conference on Robotics and …, 2005
292005
Relational object tracking and learning
D Nitti, T De Laet, L De Raedt
2014 IEEE International Conference on Robotics and Automation (ICRA), 935-942, 2014
262014
Rapid application development of constrained-based task modelling and execution using domain specific languages
D Vanthienen, M Klotzbu, J De Schutter, T De Laet, H Bruyninckx
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013
262013
Probabilistic gait classification in children with cerebral palsy: A Bayesian approach
L Van Gestel, T De Laet, E Di Lello, H Bruyninckx, G Molenaers, ...
Research in developmental disabilities 32 (6), 2542-2552, 2011
232011
A qualitative evaluation of a learning dashboard to support advisor-student dialogues
M Millecamp, F Gutiérrez, S Charleer, K Verbert, T De Laet
Proceedings of the 8th international conference on learning analytics and …, 2018
212018
Rigorously Bayesian range finder sensor model for dynamic environments
T De Laet, J De Schutter, H Bruyninckx
2008 IEEE International Conference on Robotics and Automation, 2994-3001, 2008
212008
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