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Frankfurt Additional Topics Running lecture

Systems Engineering Meets Life Sciences I

This multi-semester course focuses on emerging interdisciplinary
perspectives on ‘Systems Science and Engineering for Intelligence’. We focus on natural systems, human and computer vision, bio-inspired vision system designs, and systems theory required for modeling, analysis, simulation and validation of cognitive vision systems. The emphasis is on abstractions, modeling, and rigorous statistical approaches to performance evaluation. Connections are also made between engineering designs and architectural
designs in natural systems. The course draws upon years of systems engineering – involving systems modeling, analysis, and validation of computer vision systems and explores links them to latest viewpoints from Machine Learning, Artificial Intelligence, and Brain Sciences. The core emphasis in the course is that there is a natural correspondence between (Application Contexts, Tasks, Performance Requirements) and (Hardware and Software Programs and their Parameters). Paradigms popular for systems design – model-based systems engineering vs data-driven machine learning
will be contrasted. The course material is largely based on dissertations, publications, and online video material.
The objective of the course is to teach foundations in systems thinking that can be applied to design, analysis, and validation of intelligent systems. Through case-studies in computer vision the students learn systems modeling, simulation and optimization of intelligent systems.

Lecture + exercise, weekly

Goethe University, Frankfurt

Ramesh et al.
Winter, 4h per week / 6 ECTS

The course can be offered as a blended learning course with a distributed team project executed as a block course for one to two weeks at the end of the semester, too.