Deep learning and signal processing Two lectures at the department of

December 2, 2018 / pe

Deep learning and signal processing

Two lectures at the department of "Human Computer Interaction and Cognitive Systems"
[Picture: VIS]

Two lectures at the department of "Human Computer Interaction and Cognitive Systems"

"Deep Learning" and "Neuronal Networks" have been the topics of two lectures, that Prof. Andreas Bulling were inviting to on 28th November 2018 at the Department of "Human Computer Interaction and Cognitive Systems" of the Institute of Visualization and Interactive Systems (VIS), at the SimTech building, Pfaffenwaldring 5a.

"Deep learning" is a part of "Machine learning", that describes the way how computers improve their results with the help of the continuous training of neuronal networks. Neuronal Networks imitate the function of the human brain and refine their predictions with learning algorithms. In this context Prof. Dr.-Ing. Harald Hoppe, Laboratory of Computer-Assisted Medicine of the University of Technology Offenburg, held a lecture on "Precise and modell-free calibration of cameras and smartglasses for Augmented Reality applications in the computer-assisted surgery".

After him  Simon Hazubski, an associate of the Laboratory of the University of Technology Offenburg, focussed in his lecture on "Deep Learning in signal processing: Classification of bio signals through Long Short Term Memory Recurrent Neural Nets". Both lectures gave answers to the question, how to calibrate computer-based cameras in medical surroundings precisely with self-learning neuronal networks in order to stabilize the picture in real-time systems, e.g. for applications in surgery.

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Photo: VIS. The basis of neuronal networks in two lectures at the Department of "Human Computer Interaction and Cognitive Systems" of the University of Stuttgart.

Venue: SimTech Gebäude, Pfaffenwaldring 5a, Seminarraum 0.009 (EG)

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