About Me
Dr. Luuk Spreeuwers studied Electrical Engineering at the University of Twente, Netherlands. In 1992 he obtained his PhD from the University of Twente. The title of his PhD-thesis is: Image Filtering with Neural Networks: Applications and Performance Evaluation. Subsequently Luuk Spreeuwers worked at the International Institute for Aerospace and Earth Sciences (ITC) in Enschede, Netherlands, the University of Twente in a SION project on 3-D image analysis of aerial image sequences and in Budapest at the Hungarian Academy of Sciences in a 3-D textures ERCIM project. From 1999-2005 Luuk Spreeuwers worked on 3-D modelling and segmentation of the human heart in MRI at the Image Sciences Institute of the University Medical Centre in Utrecht, the Netherlands. Currently, he is an Associate Professor at the Data Management and Biometrics Group of the Department of EEMCS of the University of Twente, Netherlands where he is the leader of the biometrics sub-group. In addition, he is the programme mentor of the Computer Vision and Biometrics Master Specialisation and is actively involved in teaching Bachelor's and Master's courses and president of the EE Programme Committee. He was nominated 6 times for the EE Educational award and won the prize in 2018. Luuk Spreeuwers has published over 100 papers in international conferences and journals. In 2015 he published a paper on 3D face recognition where he claimed the world's best performance on a recognised benchmark in 3D face recognition. In 2017 he won the best paper award at the BIOSIG conference with the paper titled: "De-Duplication using automated Face Recognition. An accurate mathematical Model and all Babies are equally cute". He was and is involved in numerous national and European projects among which 3DFace, SOTAMD and currently iMARS. His expertise involves digital image processing and analysis, medical image analysis, biometrics and pattern recognition in general.
Expertise
Engineering & Materials Science
# Biometrics
# Cameras
# Classifiers
# Experiments
# Face Recognition
# Image Resolution
Business & Economics
# Face Recognition
# Likelihood Ratio
Organisations
Publications
Recent
Normakristagaluh, P.
, Laanstra, G. J.
, Spreeuwers, L. J.
, & Veldhuis, R. N. J. (2024).
The Impact of Illumination on Finger Vascular Pattern Recognition.
IET biometrics,
2024, Article 4413655.
https://doi.org/10.1049/2024/4413655
Sang, G.
, Zeng, D., Yan, C.
, Veldhuis, R.
, & Spreeuwers, L. (2024).
Robust partial face recognition using multi-label attributes.
Intelligent Data Analysis,
28(1), 377-392.
https://doi.org/10.3233/IDA-227309
Hoftijzer, D., Burghouts, G.
, & Spreeuwers, L. (2024).
Language-Based Augmentation to Address Shortcut Learning in Object Goal Navigation.
Spreeuwers, L., van der Grift, R.
, & Normakristagaluh, P. (2023).
3D printed realistic finger vein phantoms. ArXiv.org.
https://doi.org/10.48550/arXiv.2309.14806
Apriyanti, D. H.
, Spreeuwers, L. J.
, & Lucas, P. J. F. (2023).
Deep neural networks for explainable feature extraction in orchid identification.
Applied intelligence,
53(21), 26270-26285.
https://doi.org/10.1007/s10489-023-04880-2
Arican, T.
, Veldhuis, R.
, & Spreeuwers, L. (2023).
Exploring the Untapped Potential of Unsupervised Representation Learning for Training Set Agnostic Finger Vein Recognition. In N. Damer, M. Gomez-Barrero, K. Raja, C. Rathgeb, A. F. Sequeira, M. Todisco, & A. Uhl (Eds.),
BIOSIG 2023 - Proceedings of the 22nd International Conference of the Biometrics Special Interest Group (pp. 1-6). (Proceedings International Conference of the Biometrics Special Interest Group (BIOSIG); Vol. 2023, No. 22). IEEE.
https://doi.org/10.1109/BIOSIG58226.2023.10345775
Alsadik, B.
, Spreeuwers, L.
, Dadrass Javan, F., & Manterola, N. (2023).
Mathematical Camera Array Optimization for Face 3D Modeling Application.
Sensors,
23(24), Article 9776.
https://doi.org/10.3390/s23249776
Lestriandoko, N. H.
, Spreeuwers, L.
, & Veldhuis, R. (2023).
The Impact of Eyebrows Region on Deep Face Recognition. In
2023 10th International Conference on Computer, Control, Informatics and its Applications: Exploring the Power of Data: Leveraging Information to Drive Digital Innovation, IC3INA 2023 (pp. 319-323). IEEE.
https://doi.org/10.1109/IC3INA60834.2023.10285734
UT Research Information System
Google Scholar Link
Courses Academic Year 2023/2024
Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.
Courses Academic Year 2022/2023
Contact Details
Visiting Address
University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
(building no. 11), room 4067
Hallenweg 19
7522NH Enschede
The Netherlands
Mailing Address
University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
4067
P.O. Box 217
7500 AE Enschede
The Netherlands