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ORCIDThilo Stadelmann
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- affiliation: Zurich University of Applied Sciences, Switzerland
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2020 – today
- 2025
[i20]Pascal Sager, Benjamin Meyer, Peng Yan, Rebekka von Wartburg-Kottler, Layan Etaiwi, Aref Enayati, Gabriel Nobel, Ahmed Abdulkadir, Benjamin F. Grewe, Thilo Stadelmann:
AI Agents for Computer Use: A Review of Instruction-based Computer Control, GUI Automation, and Operator Assistants. CoRR abs/2501.16150 (2025)- 2024
- [j12]Peng Yan
, Ahmed Abdulkadir, Paul-Philipp Luley, Matthias Rosenthal, Gerrit A. Schatte, Benjamin F. Grewe, Thilo Stadelmann:
A Comprehensive Survey of Deep Transfer Learning for Anomaly Detection in Industrial Time Series: Methods, Applications, and Directions. IEEE Access 12: 3768-3789 (2024) - [j11]Felix M. Schmitt-Koopmann, Elaine M. Huang, Hans-Peter Hutter, Thilo Stadelmann, Alireza Darvishy:
MathNet: A Data-Centric Approach for Printed Mathematical Expression Recognition. IEEE Access 12: 76963-76974 (2024) - [j10]Daniel Neururer, Volker Dellwo, Thilo Stadelmann:
Deep neural networks for automatic speaker recognition do not learn supra-segmental temporal features. Pattern Recognit. Lett. 181: 64-69 (2024) - [j9]Waqar Ali, Sebastiano Vascon, Thilo Stadelmann, Marcello Pelillo:
Hierarchical Glocal Attention Pooling for Graph Classification. Pattern Recognit. Lett. 186: 71-77 (2024) - [j8]Lukas Tuggener, Raphael Emberger, Adhiraj Ghosh, Pascal Sager, Yvan Putra Satyawan, Javier A. Montoya-Zegarra, Simon Goldschagg, Florian Seibold, Urs Gut, Philipp Ackermann, Jürgen Schmidhuber, Thilo Stadelmann:
Real World Music Object Recognition. Trans. Int. Soc. Music. Inf. Retr. 7(1): 1-14 (2024) - [c40]Peter Bolt, Volker Ziebart, Christian Jaeger, Nicolas Schmid, Thilo Stadelmann, Rudolf M. Füchslin:
A Simulation Study on Energy Optimization in Building Control with Reinforcement Learning. ANNPR 2024: 320-331 - [c39]Peng Yan, Ahmed Abdulkadir, Giulia Aguzzi, Gerrit A. Schatte, Benjamin F. Grewe, Thilo Stadelmann:
Automated process monitoring in injection molding via representation learning and setpoint regression. SDS 2024: 138-145 - [c38]Lukas Tuggener, Pascal Sager, Yassine Taoudi-Benchekroun, Benjamin F. Grewe, Thilo Stadelmann:
So you want your private LLM at home? A survey and benchmark of methods for efficient GPTs. SDS 2024: 205-212 - [c37]Benjamin Meyer, Thilo Stadelmann, Marcel Lüthi:
ScalaGrad: A Statically Typed Automatic Differentiation Library for Safer Data Science. SDS 2024: 229-232 - [c36]Ahmed Begga, Waqar Ali, Gabriel Niculescu, Francisco Escolano, Thilo Stadelmann, Marcello Pelillo:
Community-Hop: Enhancing Node Classification Through Community Preference. S+SSPR 2024: 21-30 - [i19]Felix M. Schmitt-Koopmann, Elaine M. Huang, Hans-Peter Hutter, Thilo Stadelmann, Alireza Darvishy:
MathNet: A Data-Centric Approach for Printed Mathematical Expression Recognition. CoRR abs/2404.13667 (2024) - [i18]Pascal Sager, Jan Milan Deriu, Benjamin F. Grewe, Thilo Stadelmann, Christoph von der Malsburg:
The Dynamic Net Architecture: Learning Robust and Holistic Visual Representations Through Self-Organizing Networks. CoRR abs/2407.05650 (2024) - 2023
- [c35]Waqar Ali, Sebastiano Vascon, Thilo Stadelmann, Marcello Pelillo:
Quasi-CliquePool: Hierarchical Graph Pooling for Graph Classification. SAC 2023: 544-552 - [c34]Paul-Philipp Luley, Jan Milan Deriu, Peng Yan, Gerrit A. Schatte, Thilo Stadelmann:
From Concept to Implementation: The Data-Centric Development Process for AI in Industry. SDS 2023: 73-76 - [c33]Raphael Emberger, Jens Michael Boss, Daniel Baumann, Marko Seric, Shufan Huo, Lukas Tuggener, Emanuela Keller, Thilo Stadelmann:
Video Object Detection for Privacy-Preserving Patient Monitoring in Intensive Care. SDS 2023: 85-88 - [i17]Raphael Emberger, Jens Michael Boss, Daniel Baumann, Marko Seric, Shufan Huo, Lukas Tuggener, Emanuela Keller, Thilo Stadelmann:
Video object detection for privacy-preserving patient monitoring in intensive care. CoRR abs/2306.14620 (2023) - [i16]Peng Yan, Ahmed Abdulkadir, Matthias Rosenthal, Gerrit A. Schatte, Benjamin F. Grewe, Thilo Stadelmann:
A Comprehensive Survey of Deep Transfer Learning for Anomaly Detection in Industrial Time Series: Methods, Applications, and Directions. CoRR abs/2307.05638 (2023) - [i15]Daniel Neururer, Volker Dellwo, Thilo Stadelmann:
Deep Neural Networks for Automatic Speaker Recognition Do Not Learn Supra-Segmental Temporal Features. CoRR abs/2311.00489 (2023) - [i14]Lukas Tuggener, Thilo Stadelmann, Jürgen Schmidhuber:
Efficient Rotation Invariance in Deep Neural Networks through Artificial Mental Rotation. CoRR abs/2311.08525 (2023) - 2022
- [j7]Felix M. Schmitt-Koopmann, Elaine M. Huang, Hans-Peter Hutter, Thilo Stadelmann, Alireza Darvishy:
FormulaNet: A Benchmark Dataset for Mathematical Formula Detection. IEEE Access 10: 91588-91596 (2022) - [j6]Samuel Wehrli, Corinna Hertweck, Mohammadreza Amirian, Stefan Glüge, Thilo Stadelmann:
Bias, awareness, and ignorance in deep-learning-based face recognition. AI Ethics 2(3): 509-522 (2022) - [j5]Lukas Tuggener, Jürgen Schmidhuber, Thilo Stadelmann:
Is it enough to optimize CNN architectures on ImageNet? Frontiers Comput. Sci. 4 (2022) - [j4]Pascal Sager, Sebastian Salzmann, Felice Burn, Thilo Stadelmann:
Unsupervised Domain Adaptation for Vertebrae Detection and Identification in 3D CT Volumes Using a Domain Sanity Loss. J. Imaging 8(8): 222 (2022) - [i13]Christoph von der Malsburg, Thilo Stadelmann, Benjamin F. Grewe:
A Theory of Natural Intelligence. CoRR abs/2205.00002 (2022) - [i12]Mohammadreza Amirian, Javier A. Montoya-Zegarra, Jonathan Gruss, Yves D. Stebler, Ahmet Selman Bozkir, Marco Calandri, Friedhelm Schwenker, Thilo Stadelmann:
PrepNet: A Convolutional Auto-Encoder to Homogenize CT Scans for Cross-Dataset Medical Image Analysis. CoRR abs/2208.09408 (2022) - [i11]Mohammadreza Amirian, Friedhelm Schwenker, Thilo Stadelmann:
Trace and Detect Adversarial Attacks on CNNs using Feature Response Maps. CoRR abs/2208.11436 (2022) - 2021
- [c32]Mohammadreza Amirian, Javier A. Montoya-Zegarra, Jonathan Gruss, Yves D. Stebler, Ahmet Selman Bozkir, Marco Calandri, Friedhelm Schwenker, Thilo Stadelmann:
PrepNet: A Convolutional Auto-Encoder to Homogenize CT Scans for Cross-Dataset Medical Image Analysis. CISP-BMEI 2021: 1-7 - [c31]Niclas Simmler, Pascal Sager, Philipp Andermatt, Ricardo Chavarriaga, Frank-Peter Schilling, Matthias Rosenthal, Thilo Stadelmann:
A Survey of Un-, Weakly-, and Semi-Supervised Learning Methods for Noisy, Missing and Partial Labels in Industrial Vision Applications. SDS 2021: 26-31 - [c30]Evelyne Knapp, Mattia Battaglia, Thilo Stadelmann, Sandra Jenatsch, Beat Ruhstaller:
XGBoost Trained on Synthetic Data to Extract Material Parameters of Organic Semiconductors. SDS 2021: 46-51 - [i10]Lukas Tuggener, Jürgen Schmidhuber, Thilo Stadelmann:
Is it Enough to Optimize CNN Architectures on ImageNet? CoRR abs/2103.09108 (2021) - 2020
- [c29]Stefan Glüge, Mohammadreza Amirian, Dandolo Flumini, Thilo Stadelmann:
How (Not) to Measure Bias in Face Recognition Networks. ANNPR 2020: 125-137 - [c28]Lukas Tuggener, Yvan Putra Satyawan, Alexander Pacha, Jürgen Schmidhuber, Thilo Stadelmann:
The DeepScoresV2 Dataset and Benchmark for Music Object Detection. ICPR 2020: 9188-9195 - [c27]Dano Roost, Ralph Meier, Stephan Huschauer, Erik Nygren, Adrian Egli, Andreas Weiler, Thilo Stadelmann:
Improving Sample Efficiency and Multi-Agent Communication in RL-based Train Rescheduling. SDS 2020: 63-64 - [c26]Mohammadreza Amirian, Lukas Tuggener, Ricardo Chavarriaga, Yvan Putra Satyawan, Frank-Peter Schilling, Friedhelm Schwenker, Thilo Stadelmann:
Two to Trust: AutoML for Safe Modelling and Interpretable Deep Learning for Robustness. TAILOR 2020: 268-275 - [e2]Frank-Peter Schilling, Thilo Stadelmann:
Artificial Neural Networks in Pattern Recognition - 9th IAPR TC3 Workshop, ANNPR 2020, Winterthur, Switzerland, September 2-4, 2020, Proceedings. Lecture Notes in Computer Science 12294, Springer 2020, ISBN 978-3-030-58308-8 [contents] - [i9]Dano Roost, Ralph Meier, Stephan Huschauer, Erik Nygren, Adrian Egli, Andreas Weiler, Thilo Stadelmann:
Improving Sample Efficiency and Multi-Agent Communication in RL-based Train Rescheduling. CoRR abs/2004.13439 (2020)
2010 – 2019
- 2019
- [c25]Lukas Tuggener, Mohammadreza Amirian, Katharina Rombach, Stefan Lörwald, Anastasia Varlet, Christian Westermann, Thilo Stadelmann:
Automated Machine Learning in Practice: State of the Art and Recent Results. SDS 2019: 31-36 - [p8]Thilo Stadelmann, Martin Braschler, Kurt Stockinger:
Introduction to Applied Data Science. Applied Data Science 2019: 3-16 - [p7]Martin Braschler, Thilo Stadelmann, Kurt Stockinger:
Data Science. Applied Data Science 2019: 17-29 - [p6]Thilo Stadelmann, Kurt Stockinger, Gundula Heinatz Bürki, Martin Braschler:
Data Scientists. Applied Data Science 2019: 31-45 - [p5]Jürg Meierhofer, Thilo Stadelmann, Mark Cieliebak:
Data Products. Applied Data Science 2019: 47-61 - [p4]Martin Braschler, Thilo Stadelmann, Kurt Stockinger:
Organization. Applied Data Science 2019: 99-100 - [p3]Thilo Stadelmann, Vasily Tolkachev, Beate Sick, Jan Stampfli, Oliver Dürr:
Beyond ImageNet: Deep Learning in Industrial Practice. Applied Data Science 2019: 205-232 - [p2]Lukas Hollenstein, Lukas Lichtensteiger, Thilo Stadelmann, Mohammadreza Amirian, Lukas Budde, Jürg Meierhofer, Rudolf M. Füchslin, Thomas Friedli:
Unsupervised Learning and Simulation for Complexity Management in Business Operations. Applied Data Science 2019: 313-331 - [p1]Kurt Stockinger, Martin Braschler, Thilo Stadelmann:
Lessons Learned from Challenging Data Science Case Studies. Applied Data Science 2019: 447-465 - [e1]Martin Braschler, Thilo Stadelmann, Kurt Stockinger:
Applied Data Science - Lessons Learned for the Data-Driven Business. Springer 2019, ISBN 978-3-030-11820-4 [contents] - [i8]Lukas Tuggener, Mohammadreza Amirian, Katharina Rombach, Stefan Lörwald, Anastasia Varlet, Christian Westermann, Thilo Stadelmann:
Automated Machine Learning in Practice: State of the Art and Recent Results. CoRR abs/1907.08392 (2019) - 2018
- [c24]Thilo Stadelmann, Mohammadreza Amirian, Ismail Arabaci, Marek Arnold, Gilbert François Duivesteijn, Ismail Elezi, Melanie Geiger, Stefan Lörwald, Benjamin Bruno Meier, Katharina Rombach, Lukas Tuggener:
Deep Learning in the Wild. ANNPR 2018: 17-38 - [c23]Benjamin Bruno Meier, Ismail Elezi, Mohammadreza Amirian, Oliver Dürr, Thilo Stadelmann:
Learning Neural Models for End-to-End Clustering. ANNPR 2018: 126-138 - [c22]Thilo Stadelmann, Sebastian Glinski-Haefeli, Patrick Gerber, Oliver Dürr:
Capturing Suprasegmental Features of a Voice with RNNs for Improved Speaker Clustering. ANNPR 2018: 333-345 - [c21]Mohammadreza Amirian, Friedhelm Schwenker, Thilo Stadelmann:
Trace and Detect Adversarial Attacks on CNNs Using Feature Response Maps. ANNPR 2018: 346-358 - [c20]Feliks Hibraj, Sebastiano Vascon, Thilo Stadelmann, Marcello Pelillo:
Speaker Clustering Using Dominant Sets. ICPR 2018: 3549-3554 - [c19]Lukas Tuggener, Ismail Elezi, Jürgen Schmidhuber, Marcello Pelillo, Thilo Stadelmann:
DeepScores-A Dataset for Segmentation, Detection and Classification of Tiny Objects. ICPR 2018: 3704-3709 - [c18]Lukas Tuggener, Ismail Elezi, Jürgen Schmidhuber, Thilo Stadelmann:
Deep Watershed Detector for Music Object Recognition. ISMIR 2018: 271-278 - [i7]Lukas Tuggener, Ismail Elezi, Jürgen Schmidhuber, Marcello Pelillo, Thilo Stadelmann:
DeepScores - A Dataset for Segmentation, Detection and Classification of Tiny Objects. CoRR abs/1804.00525 (2018) - [i6]Feliks Hibraj, Sebastiano Vascon, Thilo Stadelmann, Marcello Pelillo:
Speaker Clustering Using Dominant Sets. CoRR abs/1805.08641 (2018) - [i5]Lukas Tuggener, Ismail Elezi, Jürgen Schmidhuber, Thilo Stadelmann:
Deep Watershed Detector for Music Object Recognition. CoRR abs/1805.10548 (2018) - [i4]Benjamin Bruno Meier, Ismail Elezi, Mohammadreza Amirian, Oliver Durr, Thilo Stadelmann:
Learning Neural Models for End-to-End Clustering. CoRR abs/1807.04001 (2018) - [i3]Thilo Stadelmann, Mohammadreza Amirian, Ismail Arabaci, Marek Arnold, Gilbert François Duivesteijn, Ismail Elezi, Melanie Geiger, Stefan Lörwald, Benjamin Bruno Meier, Katharina Rombach, Lukas Tuggener:
Deep Learning in the Wild. CoRR abs/1807.04950 (2018) - [i2]Ismail Elezi, Lukas Tuggener, Marcello Pelillo, Thilo Stadelmann:
DeepScores and Deep Watershed Detection: current state and open issues. CoRR abs/1810.05423 (2018) - 2017
- [c17]Benjamin Bruno Meier, Thilo Stadelmann, Jan Stampfli, Marek Arnold, Mark Cieliebak:
Fully Convolutional Neural Networks for Newspaper Article Segmentation. ICDAR 2017: 414-419 - [c16]Yanick X. Lukic, Carlo Vogt, Oliver Durr, Thilo Stadelmann:
Learning embeddings for speaker clustering based on voice equality. MLSP 2017: 1-6 - 2016
- [c15]Yanick X. Lukic, Carlo Vogt, Oliver Durr, Thilo Stadelmann:
Speaker identification and clustering using convolutional neural networks. MLSP 2016: 1-6 - 2015
- [j3]Jean-Daniel Dessimoz, Jana Koehler, Thilo Stadelmann:
AI in Switzerland. AI Mag. 36(2): 102-105 (2015) - [i1]Thilo Stadelmann, Mark Cieliebak, Kurt Stockinger:
Toward Automatic Data Curation for Open Data. ERCIM News 2015(100) (2015) - 2014
- [j2]Kurt Stockinger, Thilo Stadelmann:
Data Science für Lehre, Forschung und Praxis. HMD Prax. Wirtsch. 51(4): 469-479 (2014) - 2010
- [b1]Thilo Stadelmann:
Voice modeling methods for automatic speaker recognition. University of Marburg, 2010, pp. 1-237 - [c14]Christian Beecks, Thilo Stadelmann, Bernd Freisleben, Thomas Seidl:
Visual speaker model exploration. ICME 2010: 727-728 - [c13]Thilo Stadelmann, Bernd Freisleben:
Dimension-Decoupled Gaussian Mixture Model for Short Utterance Speaker Recognition. ICPR 2010: 1602-1605 - [c12]Thilo Stadelmann, Yinghui Wang, Matthew Smith, Ralph Ewerth, Bernd Freisleben:
Rethinking Algorithm Design and Development in Speech Processing. ICPR 2010: 4476-4479
2000 – 2009
- 2009
- [j1]Steffen Heinzl, Dominik Seiler, Ernst Juhnke, Thilo Stadelmann, Ralph Ewerth, Manfred Grauer, Bernd Freisleben:
A scalable service-oriented architecture for multimedia analysis, synthesis and consumption. Int. J. Web Grid Serv. 5(3): 219-260 (2009) - [c11]Dominik Seiler, Ralph Ewerth, Steffen Heinzl, Thilo Stadelmann, Markus Mühling, Bernd Freisleben, Manfred Grauer:
Eine service-orientierte Grid-Infrastruktur zur Unterstützung medienwissenschaftlicher Filmanalyse. GeNeMe 2009: 79-89 - [c10]Steffen Heinzl, Markus Mathes, Thilo Stadelmann, Dominik Seiler, Marcel Diegelmann, Helmut Dohmann, Bernd Freisleben:
The Web Service Browser: Automatic Client Generation and Efficient Data Transfer for Web Services. ICWS 2009: 743-750 - [c9]Ernst Juhnke, Dominik Seiler, Thilo Stadelmann, Tim Dörnemann, Bernd Freisleben:
LCDL: an extensible framework for wrapping legacy code. iiWAS 2009: 648-652 - [c8]Thilo Stadelmann, Bernd Freisleben:
Unfolding speaker clustering potential: a biomimetic approach. ACM Multimedia 2009: 185-194 - [c7]Markus Mühling, Ralph Ewerth, Thilo Stadelmann, Bernd Freisleben, Bing Shi:
University of Marburg at TRECVID 2009: High-Level Feature Extraction. TRECVID 2009 - 2008
- [c6]Markus Mühling, Ralph Ewerth, Thilo Stadelmann, Bernd Freisleben, Bing Shi:
University of Marburg at TRECVID 2008: High-Level Feature Extraction. TRECVID 2008 - 2007
- [c5]Markus Mühling, Ralph Ewerth, Thilo Stadelmann, Bernd Freisleben, René Weber, Klaus Mathiak:
Semantic video analysis for psychological research on violence in computer games. CIVR 2007: 611-618 - [c4]Markus Mühling, Ralph Ewerth, Thilo Stadelmann, Christian Zöfel, Bing Shi, Bernd Freisleben:
University of Marburg at TRECVID 2007: Shot Boundary Detection and High Level Feature Extraction. TRECVID 2007 - 2006
- [c3]Thilo Stadelmann, Bernd Freisleben:
Fast and Robust Speaker Clustering Using the Earth Mover'S Distance and Mixmax Models. ICASSP (1) 2006: 989-992 - [c2]Ralph Ewerth, Markus Mühling, Thilo Stadelmann, Ermir Qeli, Björn Agel, Dominik Seiler, Bernd Freisleben:
University of Marburg at TRECVID 2006: Shot Boundary Detection and Rushes Task Results. TRECVID 2006 - 2005
- [c1]Ralph Ewerth, Christian Beringer, Tobias Kopp, Michael Niebergall, Thilo Stadelmann, Bernd Freisleben:
University of Marburg at TRECVID 2005: Shot Boundary Detection and Camera Motion Estimation Results. TRECVID 2005
Coauthor Index
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