Welcome to the TMDT Hall of Fame!
Here we present TMDT's successfully completed dissertations. Learn more about the people and the research behind these accomplishments.
2023
Guided Visual Interactive Exploration and Labeling of Industrial Sensor Data, Tristan Funken, 2023
Tristan's dissertation deals with an approach for guided exploration and labeling of industrial sensor data. Using real manufacturing processes, it is shown how this approach increases efficiency in the creation of high-quality labeled data sets and thus accelerates the use of AI models for the manufacturing industry.
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Machine Learning-based Predictive Quality in Manufacturing Processes, Hasan Tercan, 2023
Hasan Tercan's dissertation investigates quality predictions in manufacturing processes using machine learning. He introduces a process model called MERLIN, which is complemented by methods such as transfer learning and continuous training to increase the data efficiency of the learning models.
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2020
Bottom-up Knowledge Graph-based Data Management, André Pomp, 2020
In this paper, a novel approach called Bottom-up Knowledge Graph is introduced, aiming to enhance semantic data management in enterprises by addressing the challenges posed by traditional ontology engineering in handling (semi-)structured data sources. Additionally, a semantic data platform (ESKAPE) is developed to demonstrate the benefits of the proposed approach.
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