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measurement and interpretation and potential usefulness in human-machine interfaces. They should learn to analyze and formally describe the problems, challenges and potential of using these signals for
Section: FB3
Course contents include brain and EEG, experiment design, signal processing, visualization, machine learning, evaluation. The course will be held as a block course during the period 10.-28.9.2018, usually
computer systems and robots that have the abilities of humans and other biological creatures, e.g. learning new facts, inferring with uncertain knowledge, understanding texts and language, visually capturing
Building Blocks for Expertise of IT Professionals in self-directed Learning Processes (Modul-IT/E-Learning) Within this project, e-Learning modules for teaching different subjects of software engineering
cable and pipe products with the help of innovative approaches from the field of Machine Learning or Deep Learning in the form of Convolutional Neural Networks. The project is being carried out in cooperation [...] Finished projects © SIKORA AG ML-X-RAY - Machine learning and X-ray technology for measuring inhomogeneous cable and pipe products BAB-Project Duration : 01.03.2021 - 31.10.2022 PI: Peter Maaß In production
robot has learned to pour juice out of a bottle and into a glass, it – unlike humans – is unable to transfer the pouring capability to other containers and substances spontaneously. It has to learn almost
worked on the fundamentals of this topic, and after 10 years, it became a mainstream topic.” “We learn so much from different people from different countries and different Institutes. It not only expands [...] in diverse perspectives.” Datta also highlights the importance of intercultural experiences: “We learn so much from different people from different countries and different Institutes. It not only expands
despite a significant and growing body of research on engaging design, many interactive systems for learning, training and, health intervention suffer from low participation and massive attrition. The present
personalised medicine. His current research also includes the development and evaluation of machine learning methods and digital health applications. He is active in serval research networks, e.g. the DFG
helmet and an EEG system (dry electrodes). The generated data is processed in real time using machine learning methods. The system is designed to detect the current attention load of the driver and to provide