Dr. Stefan Glüge
Dr. Stefan Glüge
ZHAW
School of Life Sciences and Facility Management
Institute of Computational Life Sciences
Schloss
8820 Wädenswil
Projects
- Radio Signal Unsupervised and Transfer Learning / Deputy project leader / laufend
- Emerging AI and computing technologies / Team member / abgeschlossen
- Drone Signal Dataset / Deputy project leader / abgeschlossen
- Predictive Analytics for Hospital Supply Chain Management / Team member / abgeschlossen
- PiaBreed: Machine Learning for automated ovulation and birth monitoring in horses / Deputy project leader / abgeschlossen
- Using data analysis techniques for the interpretation of stable isotope labelling incorporation from real-time PTR-ToF-MS data / Team member / abgeschlossen
- Neuronal Growth Modelling (BioDynaMo Initial Project) / Deputy project leader / abgeschlossen
- A cloud-based IoT approach for food safety and quality prediction / Team member / abgeschlossen
- Infectiology++ - Germ Tracking / Deputy project leader / abgeschlossen
- Libra: A One-Tool Solution for MLD4 Compliance / Team member / abgeschlossen
- Comprehensive Sales Forecasting for Supply Chain Optimization in Food Industry / Team member / abgeschlossen
- Multi-Asset Investment Process using Bayes Ensembles of Trading Models / Team member / abgeschlossen
- Clustering of high-throughput flow-cytometry data / Team member / abgeschlossen
Publications
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Glüge, Stefan; Nyfeler, Matthias; Aghaebrahimian, Ahmad; Ramagnano, Nicola; Schüpbach, Christof,
2024.
IEEE Journal of Radio Frequency Identification.
8, pp. 821-830.
Available from: https://doi.org/10.1109/JRFID.2024.3487303
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Körner, Paulina; Glüge, Juliane; Glüge, Stefan; Scheringer, Martin,
2024.
Environmental Science Processes & Impacts.
Available from: https://doi.org/10.1039/d4em00431k
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Epper, Pascale; Glüge, Stefan; Vidondo, Beatriz; Wróbel, Anna; Ott, Thomas; Sieme, Harald; Kaeser, Rebekka; Burger, Dominik,
2023.
Increase of body temperature immediately after ovulation in mares.
Journal of Equine Veterinary Science.
127(104565).
Available from: https://doi.org/10.1016/j.jevs.2023.104565
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Glüge, Stefan; Balabanov, Stefan; Koelzer, Viktor Hendrik; Ott, Thomas,
2023.
Evaluation of deep learning training strategies for the classification of bone marrow cell images.
Computer Methods and Programs in Biomedicine.
(243), pp. 107924.
Available from: https://doi.org/10.1016/j.cmpb.2023.107924
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Müller, Antonia; Glüge, Stefan; Vidondo, Beatriz; Wróbel, Anna; Ott, Thomas; Sieme, Harald; Burger, Dominik,
2022.
Increase of skin temperature prior to parturition in mares.
Theriogenology.
190, pp. 46-51.
Available from: https://doi.org/10.1016/j.theriogenology.2022.07.007
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Wehrli, Samuel; Hertweck, Corinna; Amirian, Mohammadreza; Glüge, Stefan; Stadelmann, Thilo,
2021.
Bias, awareness, and ignorance in deep-learning-based face recognition.
AI and Ethics.
2(3), pp. 509-522.
Available from: https://doi.org/10.1007/s43681-021-00108-6
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Juchler, Norman; Schilling, Sabine; Glüge, Stefan; Bijlenga, Philippe; Rüfenacht, Daniel; Kurtcuoglu, Vartan; Hirsch, Sven,
2020.
Computer Methods in Biomechanics and Biomedical Engineering : Imaging & Visualization.
8(5), pp. 538-546.
Available from: https://doi.org/10.1080/21681163.2020.1728579
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Glüge, Stefan; Böck, Ronald; Palm, Günther; Wendemuth, Andreas,
2014.
Neurocomputing.
141, pp. 54-64.
Available from: https://doi.org/10.1016/j.neucom.2013.11.043
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Ott, Thomas; Glüge, Stefan; Bödi, Richard; Kauf, Peter,
2019.
Economic measures of forecast accuracy for demand planning : a case-based discussion
.
In:
Braschler, Martin; Stadelmann, Thilo; Stockinger, Kurt, eds.,
Applied data science : lessons learned for the data-driven business.
Cham:
Springer.
pp. 371-386.
Available from: https://doi.org/10.1007/978-3-030-11821-1_20
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Glüge, Stefan; Nyfeler, Matthias; Ramagnano, Nicola; Horn, Claus; Schüpbach, Christof,
2023.
In:
van Stein, Niki; Marcelloni, Francesco; Lam, H.K.; Filipe, Joaquim, eds.,
Proceedings of the 15th International Joint Conference on Computational Intelligence - NCTA.
15th International Joint Conference on Computational Intelligence (IJCCI), Rome, Italy, 13-15 November 2023.
Setubal:
SciTePress.
pp. 496-504.
Available from: https://doi.org/10.5220/0012176800003595
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Frick, Thomas; Glüge, Stefan; Rahimi, Abbas; Benini, Luca; Brunschwiler, Thomas,
2021.
Explainable deep learning for medical time series data [paper].
In:
Wireless Mobile Communication and Healthcare.
International Conference on Wireless Mobile Communication and Healthcare (MobiHealth), Online, 18 December 2020.
Cham:
Springer.
pp. 244-256.
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ; 362.
Available from: https://doi.org/10.1007/978-3-030-70569-5_15
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Glüge, Stefan; Amirian, Mohammadreza; Flumini, Dandolo; Stadelmann, Thilo,
2020.
How (not) to measure bias in face recognition networks [paper].
In:
Schilling, Frank-Peter; Stadelmann, Thilo, eds.,
Artificial Neural Networks in Pattern Recognition.
9th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR'20), Winterthur, Switzerland, 2-4 September 2020.
Cham:
Springer.
Lecture Notes in Computer Science ; 12294.
Available from: https://doi.org/10.1007/978-3-030-58309-5_10
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Glüge, Stefan; Böck, Ronald; Ott, Thomas,
2017.
Emotion recognition from speech using representation learning in extreme learning machines [paper].
In:
Sabourin, Christophe; Julian Merelo, Juan; O'Reilly, Una-May; Madani, Kurosh; Warwick, Kevin, eds.,
Proceedings of the 9th International Joint Conference on Computational Intelligence.
9th International Joint Conference on Computational Intelligence, Funchal, Portugal, 1-3 November 2017.
SciTePress.
pp. 179-185.
Available from: https://doi.org/10.5220/0006485401790185
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Nef, Annina; Glüge, Stefan; Ott, Thomas; Kauf, Peter,
2014.
Causality detection in complex time dependent systems examplified in financial time series [paper].
In:
Proceedings of the 2014 International Symposium on Nonlinear Theory and its Applications (NOLTA2014).
Nonlinear Theory and Applications 2014 (NOLTA), Luzern, 14-18 September 2014.
IECE.
pp. 176-179.
Available from: http://www.ieice.org/nolta/symposium/archive/2014/nolta14fullvol.pdf
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Glüge, Stefan; Pomati, Francesco; Albert, Carlo; Kauf, Peter; Ott, Thomas,
2014.
The challenge of clustering flow cytometry data from phytoplankton in Lakes [paper].
In:
Mladenov, V.M.; Ivanov, P.C., eds.,
Nonlinear Dynamics of Electronic Systems 22nd International Conference, NDES 2014, Albena, Bulgaria, July 4-6, 2014. Proceedings.
NDES 2014, 22nd Nonlinear Dynamics of Electronic Systems Conference, Albena, Bulgaria, 4-6 July 2014.
Cham:
Springer.
pp. 379-386.
Communications in Computer and Information Science ; 438.
Available from: https://doi.org/10.1007/978-3-319-08672-9_45
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Böck, Ronald; Glüge, Stefan; Siegert, Ingo; Wendemuth, Andreas,
2013.
Annotation and classification of changes of involvement in group conversation [paper].
In:
Proceedings : 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction - ACII 2013.
ACII 2013 Humaine Association Conference, Geneva, 2-5 September 2013.
IEEE Institute of Electrical and Electronics Engineers.
pp. 803-808.
Available from: https://doi.org/10.1109/ACII.2013.150
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Ott, Thomas; Glüge, Stefan; Schüle, Martin; Hill, Christopher,
2018.
A dynamic network approach for the analysis of pathogen transmission chains.
In:
The 26th Nonlinear Dynamics of Electronic Systems Conference, (NDES 2018), Acireale, 11-13 June 2018.