Informatik

Beschreiben Sie kurz und prägnant, worum es in diesem Kurs geht.

Weiterführendes Seminar zur Vorlesung Einführung in die Funktionale Programmierung.

Anmeldung über die Selbsteinschreibung ist begrenzt auf die maximale Teilnehmerzahl, wer sich für evtl. frei werdende Plätze anmelden will, über den Anmeldebutton unter "Warteliste" anmelden.

Beschreiben Sie kurz und prägnant, worum es in diesem Kurs geht.

Beschreiben Sie kurz und prägnant, worum es in diesem Kurs geht.

Beschreiben Sie kurz und prägnant, worum es in diesem Kurs geht.

Multilingual and advanced natural language processing (NLP)
(prior NLP experience desirable, e.g., attendance of the course "Sprachverarbeitung & Text Mining" or "Machine Learning for NLP", but not necessary)

Beschreiben Sie kurz und prägnant, worum es in diesem Kurs geht.

Beschreiben Sie kurz und prägnant, worum es in diesem Kurs geht.

Beschreiben Sie kurz und prägnant, worum es in diesem Kurs geht.

Due to the technological advances in hardware and compute power nowadays the visual data is collected in huge amounts practically by everyone. The digital cameras are pervasive. Most of the smart devices include camera sensors and are capable of capturing stills and videos. With these large amounts of visual data there is a pressing need to automatically process, organize, interpret the data and refine the visual data in ways that humans are capable of. How to achieve such goals? What are the challenges? What are the solutions? What is state-of-the-art? How can we further improve the state-of-the-art? In this Praktikum Image Processing and Computational Photography, we work in groups (1 to maximum 3 participants per each group), hands-on, and for several image processing and computational photography tasks we review, explore and master the state-of-the-art under the form of the best open source solutions and further assess the pluses and minuses of these solutions and propose alternatives. Each participant will work on a specific computational photography topic of interest.

Beschreiben Sie kurz und prägnant, worum es in diesem Kurs geht.

Due to the technological advances in hardware and compute power nowadays the visual data is collected in huge amounts practically by everyone. The digital cameras are pervasive. Most of the smart devices include camera sensors and are capable of capturing stills and videos. With these large amounts of visual data there is a pressing need to automatically process, organize, interpret the data and refine the information in ways that humans are capable. Computer Vision is asked to provide such solutions.

How to achieve such goals? What are the challenges? What are the solutions? What is state-of-the-art? How can we further improve the state-of-the-art?

In this Praktikum Computer Vision, we work in groups (1 to maximum 3 participants per each group), hands-on, and for several computer vision topics we review, explore and master the state-of-the-art under the form of the best open source solutions and further assess the pluses and minuses of these solutions and propose alternatives.

Each participant will work on a specific computer vision topic of interest.

Due to the technological advances in hardware and compute power nowadays the visual data is collected in huge amounts practically by everyone. The digital cameras are pervasive. Most of the smart devices include camera sensors and are capable of capturing stills and videos. With these large amounts of visual data there is a pressing need to automatically process, organize, interpret the data and refine the information in ways that humans are capable. Computer Vision is asked to provide such solutions. How to achieve such goals? What are the challenges? What are the solutions? What is state-of-the-art? What are the benefits? What is the societal impact? How can we further improve the state-of-the-art? In this seminar, we review, explore and debate such questions based on the recent research at the intersection of Machine Learning, Computer Vision, Robotics and Artificial Intelligence. Each participant will be assigned one topic from a range of computer vision topics, including but not limited to those listed below. Each participant is expected to prepare a written review report covering the state-of-the-art on the particular topic (compiled from at least two research papers) and a corresponding oral presentation. At the same time, each participant is expected to interact, read and comment on the reports provided and presented by the other participants. Each participant will get skills on critical analysis, scientific discourse, and preparation, writing, and presentation on a research topic. Moreover, the participants will get acquainted with state-of-the-art computer vision.

In diesem Seminar wollen wir uns mit aktuellen Forschungsthemen der Algorithmische Geometrie beschäftigen. Die Algorithmische Geometrie (engl. Computational Geometry) beschäftigt sich mit algorithmischen Fragestellungen, bei denen die Ein- und/oder Ausgabedaten geometrische Objekte sind, also Punkte, Strecken, Geraden, Ebenen, Kreise, Polygone, usw. Derartige Probleme spielen in vielen Bereichen der Informatik, bei denen es notwendig ist räumliche Daten zu speichern, zu analysieren, zu erzeugen oder zu manipulieren, eine Rolle.

Beschreiben Sie kurz und prägnant, worum es in diesem Kurs geht.

Beschreiben Sie kurz und prägnant, worum es in diesem Kurs geht.

Beschreiben Sie kurz und prägnant, worum es in diesem Kurs geht.

Dear students,

all topics are taken.

- Von Reglern, Beobachtern, Schätzern und Filtern - Anhand dieser Kette von Themen ist das Ziel der Vorlesung die Herleitung und Anwendung des Kalman-Filters. Die Vorlesung wird durch Simulationsexperimente und Hardware-Experimente begleitet, um die erlernten Methoden anzuwenden und deren Möglichkeiten kennenzulernen.

Beschreiben Sie kurz und prägnant, worum es in diesem Kurs geht.