Projects

TRIPLE-nanoAUV 1 – Localisation and perception of a miniaturized autonomous underwater vehicle for the exploration of subglacial lakes

The aim of the TRIPLE project line is to design and build a system for scientific exploration of subglacial lakes while validating the associated ...

VISION – Value and Impact through Synergy, Interaction and coOperation of Networks of AI Excellence Centres

The project VISION aims to coordinate the four new AI networks of excellence selected by the European Commission in the framework of the call "Towards ...

TAILOR – Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization

The TAILOR project was selected by the European Commission in the ICT-48-2020 call for proposals "Towards a vibrant European network of AI excellence ...

HumanE-AI-Net – HumanE AI Network

The HumanE AI Network brings together European centers of excellence, universities, and key industry champions in a network of centers of excellence ...

KItatta – KI-Verfahren erkennen Qualität von Spenderhornhäuten

In Deutschland werden jährlich mehr als 9.000 Hornhauttransplantationen durchgeführt. Trotz strenger Qualitätskriterien sind bei etwa 4-5 % der ...

XAINES – Explaining AI with Narratives

In the XAINES project, the aim is not only to ensure explainability, but also to provide explanations (narratives). The central question is whether AI ...

GridAnalysis – AI-based system analysis of power distribution networks in normal and short-circuit operation - AI-based System Analysis and Assistance System

The goals of the GridAnalysis research project are the development of new models and methods for quasi-stationary and time-series-based simulation of ...

QINROS – QINROS - Quanten computing and quantum machine learning for intelligent and robotic systems

The goal of QINROS, based on the Artificial Intelligence (AI) in Quantum Computing agenda of the Robotics Working Group and DFKI RIC, is to ...

RACKET – Rare Class Learning and Unknown Events Detection for Flexible Production

The RACKET project addresses the problem of detecting rare and unknown faults by combining model-based and machine learning methods. The approach is ...

AdjUST – Automatisierung in der Konfiguration von Unternehmensinformationssystemen der Textilbranche über Methoden der KI und Referenzmodellierung

Unternehmen der Textilbranche stehen im Zuge der Digitalisierung und Globalisierung vor der Herausforderung, ihre Prozesse zu professionalisieren. ...