Current third-party/research projects
Q-AMeLiA (2020-2023): Quality Assurance of Machine Learning Applications Q-AMeLiA is a joint project of three universities and five small and medium-sized enterprises (SMEs). The goal is to support the participating companies in the special machine learning software development life cycle and the important quality indicators. Project leader: Prof. Dr. Christoph Reich |
KIEBiZ (2021-2023): AI-based solutions in endoscopy image processing: Robustness and certification Project leader: Prof. Dr. Christoph Reich |
FiSK (2021-2024): Effects of adaptive feedback bots in the simulated classroom on procedural professional knowledge Project leader: Prof. Dr. Christoph Reich |
DigNest (2021-2023): Digital Entrepreneurial Nest and Industry 4.0 in Montenegro Project leader: Prof. Dr. Christoph Reich |
Project leader: Prof. Dr. Christoph Reich |
KISS (2021-2025) – Artificial Intelligence - Services and Systems in University Education As part of a federal-state initiative to promote artificial intelligence in higher education, the extensive KISS project is funded by the German Federal Ministry of Education and Research. Project leader HFU: Prof. Dr. Stefanie Betz, Faculty of Computer Science |
KISS - sub-project led by the Faculty of Computer Science Development of learning units in the AI Competence Center Together with the University of Music, a cross-university competence center is being set up at HFU that will systematically structure teaching in the field of AI, prepare it didactically, and make it available as basic modules in the form of modern teaching formats.
Modules on programming (for example, Python) and machine learning algorithms will include using Jupyter notebooks with relevant deep learning architectures, producing short learning videos, and developing machine learning projects. Sub-project leader: Prof. Dr. Temerinac-Ott (Faculty of Computer Science), Prof. Dr. Schanbacher (Faculty of Business Information Systems)
Methods for high-quality data and process management incorporating quality assurance aspects will be addressed, which are required to simultaneously develop efficient, effective, and reliable AI systems. Sub-project leader: Prof. Dr. Christoph Reich
In socio-engineering learning units, methods and tools for sustainable, transparent and responsible AI system development are collected and prepared for concrete, reflective and ethically sound implementation. Sub-project leader: Prof. Dr. Stefanie Betz
AI teaching units and materials are created in which and with which participants can gain initial experience with the development of AI-based applications for autonomous systems. These include, for example, work units for cross-platform software development, ambient assisted living applications and AI-based emotion recognition, as well as gesture control for humanoid robots. Sub-project leader: Prof. Dr. Elmar Cochlovius |
Completed projects
KIM-Labs (2020-2021): Artificial Intelligence Mountains Labs Internal link opens in the same window:https://www.hs-furtwangen.de/forschung/forschungsprojekte/kim-lab/ |
bwGPUL (2020-2021): Provision of teaching and experimental environments for the use of GPU-based applications in teaching Internal link opens in the same window:https://www.hs-furtwangen.de/forschung/forschungsprojekte/bwgpul/ |
SensoGrind (2018-2020): In situ quality assessment of grinding processes using MST-based sensor fusion Internal link opens in the same window:https://www.hs-furtwangen.de/forschung/forschungsprojekte/sensogrind/ |
HALFBACK (2017-2020): Inter-country high-availability smart factories in the cloud Internal link opens in the same window:https://www.hs-furtwangen.de/forschung/forschungsprojekte/halfback/ |