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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Alexandria The ALEXANDRIA project (ERC Nr. 339233) aims to develop models, tools and techniques necessary to explore and analyze Web archives in a meaningful way |
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AMA - Applied Machine Learning Academy The aim of the AMA project is s to build up the Applied Machine Learning Academy (AMA) based on a sustainable, flexible and applied qualification concept |
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AutoPIN Machine learning and signal processing for automatic analysis of sensor data |
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BacData Building an analytics framework for precision microbiology to fight biofilm-associated infections |
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BIAS Bias and Discrimination in Big Data and Algorithmic Processing. Philosophical Assessments, Legal Dimensions, and Technical Solutions |
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Big Data for Cochlea Implants Understanding Cochlear Implant Outcome Variability using Big Data and Machine Learning Approaches |
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BigMedilytics Application of Big data technologies for supporting more efficient and effective healthcare systems |
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BLINKER The BLINKER project is a collaboration between L3S and Goetting KG, a company which is specialized on driverless transportation systems |
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BOOST4.0 - Big Data for Factories Big Data Value Spaces for COmpetitiveness of European COnnected Smart FacTories 4.0 |
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BRENDA II BRaunschweig ENzyme DAtabase ist das weltweit größte Informationssystem für biochemische, molekularbiologische und funktionale Enzymdaten |