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.
Mitglieder
Projekte
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Simple-ML 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
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smashHit Ensure traceability, trust, security, and privacy in data economy
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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 |
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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
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TRAVELOGUES Perceptions of the Other and the Orient in Modern Times
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MonoTo3D Developing methods for monocular depth estimation and explicit development of models inspired by human depth perception
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WildCap WildCap strives for a system to capture every possible 3d motion with mobile and moving cameras
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World-Scale Completion of Geographic Knowledge
World-Scale Completion of Geographic Knowledge |
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ZUSE-KI-mobil Energy-efficient hardware accelerator for neural networks in embedded application. |