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Intelligent systems are characterized by learning processes that allow the acquisition of new skills and deal with a large amount of heterogeneous, uncertain and probabilistic data. Due to the complexity of the real-world situations represented by them, the automatic abstraction of information from data, the formation of appropriate representative models, and the semantic processing of existing information is essential to build intelligent systems for digital transformation, such as mobility To enable industry, medicine and education.



The goal of the Simple-ML project is to significantly improve the usability of Machine Learning processes in order to make them more accessible for a braod user group





Ensure traceability, trust, security, and privacy in data economy






SMINT@Hannover – Incubator for Smart Information Technologies

The high-tech incubator SMINT supports young talents at universities and research institutions in transforming business ideas into promising business models

SoBigData: Social Mining & Big Data Ecosystem

This increasing wealth of data is a chance to disentangle social complexity and face the challenges of our world





Perceptions of the Other and the Orient in Modern Times







Developing methods for monocular depth estimation and explicit development of models inspired by human depth perception






WildCap strives for a system to capture every possible 3d motion with mobile and moving cameras









World-Scale Completion of Geographic Knowledge



World-Scale Completion of Geographic Knowledge


Energy-efficient hardware accelerator for neural networks in embedded application.