Fraunhofer CCIT Technology Hub Machine Learning

Competitive digitization applications, agile production processes and attractive new business models require a cognitive internet. It links the physical world of things with the digital world of data and learning algorithms for highly intelligent services.
 

Cognitive internet technologies – key to the digital sovereignty and economic competitiveness of German industry

With the Fraunhofer Cluster of Excellence Cognitive Internet Technologies CCIT, the Fraunhofer Gesellschaft works in three research centers on key technologies for the cognitive, industrial internet: the Technology Hubs Machine Learning,  Data Spaces and IoT-COMMs. Their aim is to establish a viable infrastructure for an agile, flexible and digitized industry.
 

New generation of reliable ML methods by including expert knowledge

The scientists of the Technology Hub Machine Learning are constantly working on innovative Machine Learning (ML) solutions in interdisciplinary projects and various application areas such as production engineering, quality control, process monitoring or dialog systems and media analysis. In doing so, the center cooperates with partners from business and industry as well as with universities and research institutions.
 

Opportunities for companies

The objective of our research is to develop a new generation of reliable ML methods that use compositional approaches to systematically integrate structural and procedural expert knowledge into statistical training processes so that they work robustly and comprehensibly even with little training data. In the long term, this will create new opportunities for companies to increase their quality and efficiency, as well as to develop new products, services, and forward-looking business models.

Do you have any questions or want to collaborate with us? We are happy to hear from you!

In the spotlight

Projects

Voice and gesture control in Industry 4.0

In the MuDA project, our scientists combined speech recognition and gesture control into a multimodal voice assistant that can be used for defect identification and marking. New forms of interaction with technical devices and user interfaces via gestures and speech have great potential in industry to make processes more efficient and intuitive.  

 
 

Research

Into a new dimension with Informed ML

Three questions for Prof. Dr. Stefan Wrobel, Director of the Machine Learning Technology Hub

Publications

Get an impression of our research work

Discover all publications of our scientists at the Technology Hub Machine Learning.