Applied Machine Learning

The Applied Machine Learning group aims to develop and apply novel Machine Learning methods for real-world applications. Emerging digitalization allows companies from different fields of industry to produce and collect data from various resources. This is realized by technologies like the Internet of Things (IoT), cyber-physical systems and cloud-computing. To effectively handle this big data, Deep Learning and Signal Processing techniques are needed to provide powerful and promising solutions.

Group Head

Dr. Dario Zanca

Room 01.016

Phone number: +49 9131 85-20296
Email: dario.zanca@fau.de

Students

If you are interested in writing a Bachelor’s or Master’s thesis in our group, please check the lab’s Student Theses and Jobs.

Björn Nieth
Incorporating data pruning into robust learning with large-scale datasets
Moumita Chakraborty
Are click explorations a valid alternative to eye tracking?
Lukas Böhm
Developing New Approaches For Measuring Invariances Between Models Using Model Metamers
Paula Limmer
Development and Evaluation of an Application for Patient-Specific Contrast Media Computation in CT Scans

Past Students

Nils Steinlein
The creation and evaluation of a video-based polar bear Re-Identification dataset on current Re-ID methods
Sara Zarifi
Lynx Re-Identification from Camera Trap Images in the Wild

Projects

Completed Projects

Publications

2024

Abdelaal M., Yayak AB., Klede K., Schöning H.:
ReClean: Reinforcement Learning for Automated Data Cleaning in ML Pipelines
3rd International Workshop on Databases and Machine Learning (Utrecht, 13. May 2024 - 13. May 2024)
Open Access: https://www.wis.ewi.tudelft.nl/assets/files/dbml2024/DBML24_paper_11.pdf
URL: https://www.wis.ewi.tudelft.nl/assets/files/dbml2024/DBML24_paper_11.pdf
BibTeX: Download
Küderle A., Ullrich M., Roth N., Ollenschläger M., Ibrahim A., Moradi H., Richer R., Seifer AK., Zürl M., Simpetru R., Herzer L., Prossel D., Kluge F., Eskofier B.:
Gaitmap – An Open Ecosystem for IMU-based Human Gait Analysis and Algorithm Benchmarking
In: IEEE Open Journal of Engineering in Medicine and Biology (2024), p. 1-10
DOI: 10.1109/OJEMB.2024.3356791
BibTeX: Download

2023

Abdullahi I., Raab R., Küderle A., Eskofier B.:
Aligning Federated Learning with Existing Trust Structures in Health Care Systems
In: International Journal of Environmental Research and Public Health 20 (2023), Article No.: 5378
ISSN: 1661-7827
DOI: 10.3390/ijerph20075378
URL: https://www.mdpi.com/1660-4601/20/7/5378
BibTeX: Download
Altstidl TR., Nguyen AT., Schwinn L., Köferl F., Mutschler C., Eskofier B., Zanca D.:
Just a Matter of Scale? Reevaluating Scale Equivariance in Convolutional Neural Networks
2023 International Joint Conference on Neural Networks (IJCNN) (Gold Coast, Australia, 18. June 2023 - 23. June 2023)
In: Proc. Intl. Joint Conf. Neural Netw. (IJCNN) 2023
DOI: 10.1109/IJCNN54540.2023.10191724
BibTeX: Download
Dumbach P., Schwinn L., Löhr T., Do PL., Eskofier B.:
Artificial intelligence trend analysis on healthcare podcasts using topic modeling and sentiment analysis: a data-driven approach
In: Evolutionary Intelligence (2023)
ISSN: 1864-5909
DOI: 10.1007/s12065-023-00878-4
URL: https://link.springer.com/article/10.1007/s12065-023-00878-4
BibTeX: Download
Dumbach P., Schwinn L., Löhr T., Elsberger T., Eskofier B.:
Artificial intelligence trend analysis in German business and politics: a web mining approach
In: International Journal of Data Science and Analytics (2023), p. 1-22
ISSN: 2364-415X
DOI: 10.1007/s41060-023-00483-9
URL: https://link.springer.com/article/10.1007/s41060-023-00483-9
BibTeX: Download
Klede K., Altstidl TR., Zanca D., Eskofier B.:
p-value Adjustment for Monotonous, Unbiased, and Fast Clustering Comparison
Thirty-seventh Annual Conference on Neural Information Processing Systems (New Orleans, 10. December 2023 - 16. December 2023)
In: A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine (ed.): Advances in Neural Information Processing Systems 36 2023
Open Access: https://proceedings.neurips.cc/paper_files/paper/2023/file/563d94819f68cb73d6a382809e587b54-Paper-Conference.pdf
URL: https://proceedings.neurips.cc/paper_files/paper/2023/file/563d94819f68cb73d6a382809e587b54-Paper-Conference.pdf
BibTeX: Download
Klede K., Schwinn L., Zanca D., Eskofier B.:
FastAMI - A Monte Carlo Approach to the Adjustment for Chance in Clustering Comparison Metrics
AAAI 2023 (Washington, D.C., 7. February 2023 - 14. February 2023)
In: Proceedings of the AAAI Conference on Artificial Intelligence, 37(7) 2023
DOI: 10.1609/aaai.v37i7.26003
URL: https://ojs.aaai.org/index.php/AAAI/article/view/26003
BibTeX: Download
Maier T., Kamm L., Heckmann A., Eskofier B.:
Homogeneous Soil Moisture Sensor with High Repeatability for Different Soil Depths
Sensor and Measurement Science International 2023 (Nuremberg, Germany, 8. May 2023 - 11. May 2023)
DOI: 10.5162/smsi2023/p32
BibTeX: Download
Raab R., Küderle A., Zakreuskaya A., Stern AD., Klucken J., Kaissis G., Rueckert D., Boll S., Eils R., Wagener H., Eskofier B.:
Federated electronic health records for the European Health Data Space
In: The Lancet Digital Health 5 (2023), p. e840-e847
ISSN: 2589-7500
DOI: 10.1016/S2589-7500(23)00156-5
URL: https://www.thelancet.com/journals/landig/article/PIIS2589-7500(23)00156-5/fulltext
BibTeX: Download
Schwinn L., Raab R., Nguyen A., Zanca D., Eskofier B.:
Exploring misclassifications of robust neural networks to enhance adversarial attacks
In: Applied Intelligence (2023)
ISSN: 0924-669X
DOI: 10.1007/s10489-023-04532-5
BibTeX: Download
Zugarini A., Röthenbacher T., Klede K., Ernandes M., Eskofier B., Zanca D.:
Die Rätselrevolution: Automated German Crossword Solving
CLiC-it 2023 - Italian Conference on Computational Linguistics (Venice, 30. November 2023 - 2. December 2023)
In: Federico Boschetti, Gianluca E. Lebani, Bernardo Magnini, Nicole Novielli (ed.): Proceedings of the 9th Italian Conference on Computational Linguistics 2023
Open Access: https://ceur-ws.org/Vol-3596/paper54.pdf
URL: https://ceur-ws.org/Vol-3596/paper54.pdf
BibTeX: Download
Zürl M., Dirauf R., Köferl F., Steinlein N., Sueskind J., Zanca D., Brehm I., von Fersen L., Eskofier B.:
PolarBearVidID: A Video-Based Re-Identification Benchmark Dataset for Polar Bears
In: Animals 13 (2023), p. 801
ISSN: 2076-2615
DOI: 10.3390/ani13050801
BibTeX: Download

2022

Hecht D., Pfahler T., Ullmann I., Altstidl TR., Amer N., Jin Y., Eskofier B., Vossiek M.:
In Vivo Skin-Type Classification Using Millimeter-Wave Near-Field Probe Spectroscopy
2022 52nd European Microwave Conference (Milan, 27. September 2022 - 29. September 2022)
In: Institute of Electrical and Electronics Engineers (IEEE) (ed.): 2022 52nd European Microwave Conference, Milan: 2022
DOI: 10.23919/EuMC54642.2022.9924376
BibTeX: Download
Schwinn L., Bungert L., Nguyen A., Raab R., Pulsmeyer F., Precup D., Eskofier B., Zanca D.:
Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification
Proceedings of the 39th International Conference on Machine Learning (Baltimore, USA, 17. July 2022 - 23. July 2022)
In: PMLR (ed.): 162 2022
Open Access: https://proceedings.mlr.press/v162/schwinn22a.html
URL: https://proceedings.mlr.press/v162/schwinn22a.html
BibTeX: Download
Zürl M., Stoll P., Brehm I., Raab R., Zanca D., Kabri S., Happold J., Nille H., Prechtel K., Wünsch S., Krause M., Seegerer S., von Fersen L., Eskofier B.:
Automated Video-Based Analysis Framework for Behavior Monitoring of Individual Animals in Zoos Using Deep Learning—A Study on Polar Bears
In: Animals 12 (2022), p. 692
ISSN: 2076-2615
DOI: 10.3390/ani12060692
BibTeX: Download

2021

Altstidl TR., Kram S., Herrmann O., Stahlke M., Feigl T., Mutschler C.:
Accuracy-Aware Compression of Channel Impulse Responses using Deep Learning
International Conference on Indoor Positioning and Indoor Navigation (IPIN2021) (Lloret de Mar, 29. November 2021 - 2. December 2021)
In: Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN 2021) 2021
DOI: 10.1109/IPIN51156.2021.9662545
BibTeX: Download
Bungert L., Raab R., Roith T., Schwinn L., Tenbrinck D.:
CLIP: Cheap Lipschitz Training of Neural Networks
International Conference on Scale Space and Variational Methods in Computer Vision
In: Abderrahim Elmoataz, Jalal Fadili, Yvain Quéau, Julien Rabin, Loïc Simon (ed.): SSVM 2021: Scale Space and Variational Methods in Computer Vision, Cham: 2021
DOI: 10.1007/978-3-030-75549-2_25
URL: https://arxiv.org/abs/2103.12531
BibTeX: Download
Dumbach P., Liu R., Jalowski M., Eskofier B.:
The Adoption Of Artificial Intelligence In SMEs - A Cross-National Comparison In German And Chinese Healthcare
20th International Conference on Perspectives in Business Informatics Research (BIR 2021) Workshops (ILOG 2021) (Vienna, Austria (fully-virtual conference), 22. September 2021 - 24. September 2021)
In: Forbig P., Hinkelmann K., Kirikova M., Lantow B., Møller C., Morichetta A., Plebani P., Re B., Sandkuhl K., Seigerroth U. (ed.): Joint Proceedings of the BIR 2021 Workshops and Doctoral Consortium co-located with 20th International Conference on Perspectives in Business Informatics Research (BIR 2021) 2021
URL: http://ceur-ws.org/Vol-2991/paper08.pdf
BibTeX: Download
Laut P., Dumbach P., Eskofier B.:
Integration of Artificial Intelligence in the Organizational Adoption – A Configurational Perspective
Forty-Second International Conference on Information Systems (Austin, 11. December 2021 - 15. November 2021)
In: Association for Information Systems (ed.): ICIS 2021 Proceedings 2021
URL: https://aisel.aisnet.org/icis2021/is_implement/is_implement/2/
BibTeX: Download
Schwinn L., Nguyen A., Raab R., Bungert L., Tenbrinck D., Zanca D., Burger M., Eskofier B.:
Identifying untrustworthy predictions in neural networks by geometric gradient analysis
Conference on Uncertainty in Artificial Intelligence (UAI) (Online, 27. July 2021 - 30. July 2021)
URL: https://arxiv.org/abs/2102.12196
BibTeX: Download
Schwinn L., Nguyen A., Raab R., Zanca D., Eskofier B., Tenbrinck D., Burger M.:
Dynamically Sampled Nonlocal Gradients for Stronger Adversarial Attacks
International Joint Conference on Neural Networks (IJCNN) (Online, 18. July 2021 - 22. July 2021)
DOI: 10.1109/ijcnn52387.2021.9534190
BibTeX: Download
Schwinn L., Raab R., Nguyen A., Zanca D., Eskofier B.:
Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks
URL: https://arxiv.org/abs/2105.10304
BibTeX: Download

2020

Dumbach P., Aly A., Zrenner M., Eskofier B.:
Exploration of Process Mining Opportunities In Educational Software Engineering - The GitLab Analyser
13th International Conference on Educational Data Mining (Ifrane, Morocco (Fully Virtual Conference), 10. July 2020 - 13. July 2020)
In: Anna N. Rafferty, Jacob Whitehill, Cristobal Romero, Violetta Cavalli-Sforza (ed.): Proceedings of the 13th International Conference on Educational Data Mining 2020
Open Access: https://educationaldatamining.org/files/conferences/EDM2020/papers/paper_239.pdf
URL: https://educationaldatamining.org/files/conferences/EDM2020/EDM2020Proceedings.pdf
BibTeX: Download
Groß T., Dirauf R., Freiling F.:
Systematic Analysis of Browser History Evidence
13th International Conference on Systematic Approaches to Digital Forensic Engineering (SADFE) (New York, 15. May 2020 - 15. May 2020)
In: IEEE (ed.): 2020 13th International Conference on Systematic Approaches to Digital Forensic Engineering (SADFE) 2020
DOI: 10.1109/SADFE51007.2020.00010
BibTeX: Download
Köferl F., Link J., Eskofier B.:
Application of SORT on Multi-Object Tracking and Segmentation
Conference on Computer Vision and Pattern Recognition; 5th BMTT MOTChallenge Workshop: Multi-Object Tracking and Segmentation (Seattle, WA, USA (Virtual), 19. June 2020 - 19. June 2020)
URL: https://motchallenge.net/workshops/bmtt2020/papers/Application_and_Adaptations_of_SORT_on_MOTS20.pdf
BibTeX: Download
(Working Paper)
Rüthlein M., Köferl F., Mehringer W., Eskofier B.:
Interactive Segmentation of RGB-D Indoor Scenes using Deep Learning
International Conference on Machine Learning; 2nd ICML 2020 Workshop on Human in the Loop Learning (Virtual Conference, 18. July 2020 - 18. July 2020)
BibTeX: Download
(Conference report)

2019

Raab R., Driessens K.:
A generative policy gradient approach for learning to play text-based adventure games
BNAIC/BENELEARN 2019 (Brussels, 6. November 2019 - 8. November 2019)
In: Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019) 2019
Open Access: http://ceur-ws.org/Vol-2491/abstract18.pdf
BibTeX: Download

2017

Maier T., Kamm L.:
Moisture Sensor for Gravitation Dependent Plant Watering
68th International Astronautical Conference (IAC) (Adelaide, Australia, 25. September 2017 - 29. September 2017)
URL: https://www.researchgate.net/publication/319939522_Moisture_sensor_for_gravitation_dependent_plant_watering
BibTeX: Download

2016

Maier T., Kamm L.:
Capacitive Soil Moisture Sensor for Plant Watering
European Geosciences Union (EGU) 2016 General Assembly (Wien, Österreich, 17. April 2016 - 22. April 2016)
URL: https://meetingorganizer.copernicus.org/EGU2016/EGU2016-13805.pdf?pdf/https://meetingorganizer.copernicus.org/EGU2016/EGU2016-13805.pdf?pdf
BibTeX: Download

2015

Selgrad K., Lier A., Köferl F., Stamminger M., Lohmann D.:
Lightweight, generative variant exploration for high-performance graphics applications
14th International Conference on Generative Programming: Concepts & Experiences (GPCE) (Pittsburgh, PA, 26. October 2015 - 27. October 2015)
In: ACM Bd. 51, Nr. 3 2015
DOI: 10.1145/2814204.2814220
BibTeX: Download