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
|
Haisem Lab Labor for methodical development of high-performance AI-applications for modern hardware-Architectures
|
|
iASiS Big Data for precision medicine
|
|
IIP-Ecosphere: Next Level Ecosphere for Intelligent Industrial Production IIP-Ecosphere: Next Level Ecosphere for Intelligent Industrial Production
|
|
InclusiveOCW Inclusive, collaborative creation and usage of open courseware in the professional promotion of people with visual impairments
|
|
Industrial Data Acquisition Solution (INDAAQ) INDAAQ deals with industrial data and its implementation in the manufacturing process
|
|
Internationales Zukunftslabor Künstliche Intelligenz International Future Lab for Artificial Intelligence
|
|
Maschinelles Lernen Fähigkeiten für IKT-Fachleute MACHINA project aims to enhance Vocational Education and Training for ICT professionals in the field of Machine learning.
|
|
Managed Forgetting Today's flood of information makes it more and more difficult to concentrate on the really relevant and important things.
|
|
MIRROR From perception to expectation to realization: comprehensive intermedia analysis on misinformation when migrating into the EU and potentially resulting threats.
|
|
MM4SPA Intelligent synchronization and semantic enrichment of position and video data for the analysis of sports gamesa
|