prenode actively contributes know-how on machine learning and AI development in various research projects. Through our position in the advisory boards of two collaborative projects, we can exchange cross-domain knowledge. This enables us to provide expertise on tech topics and learn about the needs and requirements of the involved partners.
Specifically, we are involved in the “Intelligent Diagnostics” program of the Innovation Alliance BW and the “IMPRESS” project from Hahn-Schickard and Hohenstein Institute of Textile Innovation.
The project “Intelligent Diagnostics” aims to detect skin tumors with the help of AI. Traditionally, these medical diagnoses require specifically trained staff. An AI-assisted approach could make such screenings accessible for a broader audience.
However, the development requires high-quality medical data. This is crucial for model training and especially important, since the patients’ data has to be kept private. At this point prenode’s decentralized approach comes into play: by using Federated Learning and Transfer Learning, we enable the development of ML models at separate locations without the centralization of sensitive data.
More information on the project at the innBW website.
The project is carried out conjointly by:
Support and funding are provided by Ministry of Economic Affairs, Labour and Housing Baden-Württemberg.
The “IMPRESS” project focuses on process automation in commercial washeries. For the development of an intelligent monitoring concept, a system of sensors is combined with an AI-based control component.
The AI-based steering could increase both process quality and resource efficiency of the washeries. prenode helps in the development of ML models across different facilities. Ultimately, a successful implementation of the system could pave the way for further intelligent automation in this sector.
Find out more about the project at the website of Hahn-Schickard.
Funding is provided by the Federal Ministry for Economic Affairs and Energy.
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