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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.

Projekte

d-E-mand

Prediction of electric vehicle charging demand as business enabler

 

 

 

 

Data4UrbanMobility

Data4UrbanMobility focuses on facilitating innovative mobility services and mobility-related infrastructure development in smart cities through comprehensive data analytics

 

 

 

 

 

Discovering Job Knowledge from Web Data

Discovering Job Knowledge from Web Data

 

 

EAST-CITIES

Establishing and achieving sustainable targets in Eastern Chinese cities

 

 

 

eLabour II

Interdisciplinary Centre for IT-based Qualitative Research in Work Sociology

 

 

ErrorlessLearning

Project extention for a orthograhic training methode

 

 

 

 

ZL Produktion

Digital modelling and optimization

 

 

 

Haisem Lab

Labor for methodical development of high-performance AI-applications for modern hardware-Architectures

 

 

 

 

 

iASiS

Big Data for precision medicine

 

 

 

InclusiveOCW

Inclusive, collaborative creation and usage of open courseware in the professional promotion of people with visual impairments