DiDiER - digitized services in dietary counselling for people with increased health risks related to malnutrition and food allergies. - Patrick Elfert; Marco Eichelberg; Johannes Tröger; Jochen Britz; Jan Alexandersson; Daniel Bieber; Jürgen M. Bauer; Susanne Teichmann; Ludwig Kuhn; Martin Thielen; Janina Sauer; Alexander Münzberg; et al. (ISCC, 2017)

The use of ETL and data profiling to integrate data and improve quality in food databases. - Alexander Münzberg; Janina Sauer; Andreas Hein 001; Norbert Rösch (WiMob, 2018)

Intelligent Combination of Food Composition Databases and Food Product Databases for Use in Health Applications. - Alexander Münzberg; Janina Sauer; Andreas Hein 001; Norbert Rösch (MobiHealth, 2019)

Remote Testing of Usability in Medical Apps. - Janina Sauer; Alexander Münzberg; Laura Siewert; Andreas Hein 001; Norbert Rösch (MobiHealth, 2019)

Checking the Plausibility of Nutrient Data in Food Datasets Using KNIME and Big Data. - Alexander Münzberg; Janina Sauer; Andreas Hein 001; Norbert Rösch (WiMob, 2019)

Simplify Testing of Mobile Medical Applications by Using Timestamps for Remote, Automated Evaluation. - Janina Sauer; Andreas Hein 001; Alexander Münzberg; Norbert Rösch (WiMob, 2019)

Machine Learning and Context-Based Approaches to Get Quality Improved Food Data. - Alexander Münzberg; Janina Sauer; Andreas Hein 001; Norbert Rösch (ICICT (2), 2021)

Increase the Quality of Treatment with Medical Apps Through Remote Compliance Testing. - Janina Sauer; Alexander Münzberg; Franz Reisewitz; Andreas Hein 001; Norbert Rösch (ICICT (1), 2021)

Machine Learning on Simulated and Real Farm Data Based on an Ontology-Controlled Data Infrastructure. - Alexander Münzberg; Christian Troost; Daniel Martini; Francisco Mendoza 004; Rajiv Kumar Srivastava; Thomas Berger; Liv Seuring; Nils Reinosch; Thilo Streck; Ansgar Bernardi (AAAI Spring Symposium: MAKE, 2022)

Using Transfer Learning for Quality Improved Forecasting of Temporal Agricultural Processes by Adapting Convolutional Neural Networks. - Alexander Münzberg; Christian Troost; Ansgar Bernardi (GI-Jahrestagung, 2022)

Konzeption und Entwicklung einer Datenbasis für Gesundheits-Apps mit qualitätsgeprüften Lebensmitteldaten aus externen Quellen. - Alexander Münzberg (2022)

Landwirtschaftliche Ertragsvorhersage im Kontext begrenzter realer Trainingsdatensätze: ein Transfer-Learning-Ansatz unter Verwendung tieferneuronalerNetze. - Alexander Münzberg; Christian Troost; Nils Reinosch; Daniel Martini; Liv Seuring; Alexander Niehus; Rajiv Kumar Srivastava; Thilo Streck; Thomas Berger; Ansgar Bernardi (GI-Jahrestagung, 2023)

SIMLEARN - Ontologiegestützte Integration von Simulationsmodellen, Systemen für maschinelles Lernen und Planungsdaten. - Nils Reinosch; Alexander Münzberg; Daniel Martini; Alexander Niehus; Liv Seuring; Christian Troost; Rajiv Kumar Srivastava; Thomas Berger; Thilo Streck; Ansgar Bernardi (GIL Jahrestagung, 2023)