HS2018

The goal of the course is to put Information and Communication Technology (ICT) and Informatics as Science in perspective of human, natural, cognitive and meta sciences, namely through domains like the anthropology of the technique, the philosophy of the technique, interaction and communication, many fields in life sciences, ethics and system science. The benefits are cross-fertilization between the models and worldviews of these domains and Informatics, in order to pave the way towards interdisciplinary and integral (or holistic) design methodologies in ICT, and a worldview able to integrate the contribution of Informatics to the XXI century scientific landscape. The pedagogical methodology combines theoretical insights and pragmatic approaches, possibly up to innovative workshops. The main outcomes of the course are: Holistic understanding of computer technology, engineering and informatics Better ability to work in interdisciplinary teams Ability to use models and methods inspired by or coming from other disciplines in Design in ICT and Informatics Development of system thinking and integral thinking Better ability to self-position in future professional life.

See http://scg.unibe.ch/teaching/sma

http://scg.unibe.ch/wiki/softwarecompositionseminar

This course covers fundamental topics in computer vision. The course will provide an introduction to image formation, image processing, feature detection, segmentation, multiple view geometry and 3D reconstruction, motion, object recognition and classification. The following books are recommended as additional reading: • Computer Vision : A Modern Approach, David A. Forsyth and Jean Ponce. • Algorithms and Applications, Rick Szeliski. • Visual Object Recognition, Kristen Grauman and Bastian Leibe.

In this course, we first introduce some basic concepts and notions of graph theory. We then present a series of graph theoretical problems (vertex coloring, edge coloring, maximum matching, …) which have real world applications (in sports scheduling, timetabling, transmission problems, … ) and focus on how these problems may be solved. We will also consider special graph classes and see how some of the before mentioned problems can be solved in these classes. Finally, the students will also learn how to model other real world problems using the graph theoretical notions introduced. Learning outcomes: With this course, the students will get familiar with the basic notions and fundamental problems in graph theory. They will learn how to use these theoretical problems to model real world problems as well as how to solve them.