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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

Ganzheitliche Szenenanalyse

InclusiveOCW

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

Interpreting Neural Rankers

Understanding decisions made by Deep Learned Models in Information Retrieval
(Amazon Research Grant)

Managed Forgetting

Die heutige Informationsflut erschwert es immer mehr, sich auf die wirklich relevanten und wichtigen Dinge zu konzentrieren

OSCAR

Opinion Stream Classification with Ensembles and Active learners

Regio

ScienceGRAPH

Knowledge Graph based Representation, Augmentation and Exploration of Scholarly Communication

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.

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

TRAVELOUGES