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Recent
Zubavicius, R.
, Alveringh, D.
, Poel, M.
, Groenesteijn, J.
, Sanders, R. G. P.
, Wiegerink, R. J.
, & Lötters, J. C. (2024).
Machine learning-enhanced mass flow measurements using a Coriolis mass flow sensor. In
The 5th Conference On MicroFluidic Handling Systems (MFHS 2024) (pp. 65-68)
Zubavicius, R.
, Alveringh, D.
, Poel, M.
, Groenesteijn, J.
, Sanders, R. G. P.
, Wiegerink, R. J.
, & Lötters, J. C. (2024).
Fluid Viscosity and Density Determination With Machine Learning-Enhanced Coriolis Mass Flow Sensors. In
2024 IEEE 37th International Conference on Micro Electro Mechanical Systems (MEMS) (pp. 82-85). IEEE.
https://doi.org/10.1109/MEMS58180.2024.10439597
van de Beld, J.-J., Crull, D., Mikhal, J., Geerdink, J., Veldhuis, A.
, Poel, M., & Kouwenhoven, E. A. (2024).
Complication Prediction after Esophagectomy with Machine Learning.
Diagnostics,
14(4), Article 439.
https://doi.org/10.3390/diagnostics14040439
Schulte, R. V.
, Prinsen, E. C., Schaake, L., Paassen, R. P. G., Zondag, M.
, Staveren, E. S. V.
, Poel, M.
, & Buurke, J. H. (2023).
Database of lower limb kinematics and electromyography during gait-related activities in able-bodied subjects.
Scientific Data,
10, Article 461.
https://doi.org/10.1038/s41597-023-02341-6
Schulte, R. V. (2022).
Up to one's knees in data: Data-driven intent recognition using electromyography for the lower limb. [PhD Thesis - Research external, graduation UT, University of Twente]. University of Twente.
https://doi.org/10.3990/1.9789036554862
Schulte, R. V.
, Prinsen, E. C.
, Buurke, J. H.
, & Poel, M. (2022).
Adaptive Lower Limb Pattern Recognition for Multi-Day Control.
Sensors,
22(17), Article 6351.
https://doi.org/10.3390/s22176351
Verma, D., Jansen, D., Bach, K.
, Poel, M., Mork, P. J.
, & d'Hollosy, W. (2022).
Exploratory application of machine learning methods on patient reported data in the development of supervised models for predicting outcomes.
BMC medical informatics and decision making,
22, Article 227.
https://doi.org/10.1186/s12911-022-01973-9
Botteghi, N., Grefte, L.
, Poel, M.
, Sirmacek, B.
, Brune, C.
, Dertien, E.
, & Stramigioli, S. (2022).
Towards Autonomous Pipeline Inspection with Hierarchical Reinforcement Learning. In J. Kim, B. Englot, H.-W. Park, H.-L. Choi, H. Myung, J. Kim, & J.-H. Kim (Eds.),
Robot Intelligence Technology and Applications 6 - Results from the 9th International Conference on Robot Intelligence Technology and Applications (pp. 259-271). (Lecture Notes in Networks and Systems; Vol. 429 LNNS). Springer.
https://doi.org/10.1007/978-3-030-97672-9_23
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Master
Vakken Collegejaar 2023/2024
Vakken in het huidig collegejaar worden toegevoegd op het moment dat zij definitief zijn in het Osiris systeem. Daarom kan het zijn dat de lijst nog niet compleet is voor het gehele collegejaar.
Vakken Collegejaar 2022/2023
Contactgegevens
Bezoekadres
Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
(gebouwnr. 11), kamer 4102
Hallenweg 19
7522NH Enschede
Postadres
Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
4102
Postbus 217
7500 AE Enschede