Zilverling

dr.ir. L.J. Spreeuwers (Luuk)

Associate Professor
EEMCS-CS-DMB
Zilverling 4067
l.j.spreeuwers@utwente.nl
+31534893368
Business card

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

  • Computer Science

    • Face Recognition
    • Recognition System
    • Biometrics
    • Morphing
    • Forensics
    • Attack
    • Database
    • Detection

Organisations

Publications

2025

Explainable automated wild-orchid identification combining deep neural networks and Bayesian networks (2025)Engineering applications of artificial intelligence, 161. Article 111961. Apriyanti, D. H., Spreeuwers, L. J. & Lucas, P. J. F.https://doi.org/10.1016/j.engappai.2025.111961Side-view face recognition (2025)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Santemiz, P.https://doi.org/10.3990/1.9789036567688Vision on the Move: Automated Hazardous Material Plate Detection in Freight Transport (2025)In Computer Analysis of Images and Patterns: 21st International Conference, CAIP 2025, Proceedings (pp. 259-270) (Lecture Notes in Computer Science; Vol. 15621). Springer (E-pub ahead of print/First online). Tijink, M., Levendeev, S., Nieuwenhuis, E., Spreeuwers, L., Strisciuglio, N. & Talavera, E.https://doi.org/10.1007/978-3-032-04968-1_22The contribution of facial components to face recognition (2025)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Lestriandoko, N. H.https://doi.org/10.3990/1.9789036567923StyleDemorpher: high-quality face demorphing via StyleGAN2’s latent space (2025)Machine vision and applications, 36(5). Article 113. Ismayilov, R., Spreeuwers, L. & Batskos, I.https://doi.org/10.1007/s00138-025-01735-3FLUXSynID: A Framework for Identity-Controlled Synthetic Face Generation with Document and Live Images (2025)[Working paper › Preprint]. ArXiv.org. Ismayilov, R., Sero, D. & Spreeuwers, L.https://doi.org/10.48550/arXiv.2505.07530FLUXSynID: A Synthetic Face Dataset with Document and Live Images (2025)[Dataset Types › Dataset]. Zenodo. Ismayilov, R., Spreeuwers, L. & Sero, D.https://doi.org/10.5281/zenodo.15172769Accelerating Selective Sweep Detection using AMD Deep Learning Processing Units and Vitis AI (2025)In 45th Symposium on Information Theory and Signal Processing (SITB 2025) (pp. 8-11) (Accepted/In press). Bunda, S., Alachiotis, N. & Spreeuwers, L.Towards explainable orchid flower identification (2025)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Apriyanti, D. H.https://doi.org/10.3990/1.9789036565684The problem of face image morphing in identification documents: Analysis, prevention and detection (2025)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Batskos, I.https://doi.org/10.3990/1.9789036565622

Research profiles

Courses academic year 2025/2026

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 2024/2025

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