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Applied Visualization (AppVis)
- Dozent/in
- Prof. Dr.-Ing. Tobias Günther
- Angaben
- Vorlesung
2 SWS, benoteter Schein, ECTS-Studium, ECTS-Credits: 5,0
nur Fachstudium, Sprache Englisch
Zeit und Ort: Do 10:15 - 11:45, H4
- Studienfächer / Studienrichtungen
- WPF MT-MA-BDV 1-2
WF CE-MA-INF ab 1
WF CE-BA-TW ab 4
WPF INF-BA-V-GD 4-6
WPF INF-MA ab 1
WPF IuK-MA-MMS-INF 1-3
WPF ICT-MA-MPS 1-4
WPF MB-BA-FG13 4-6
WPF MB-MA-FG13 1-3
WF WW-BAH 6
WF WW-DH ab 6
WF MWT-MA-AWE ab 1
WF LSE-MA ab 1
WPF PG-BA ab 3
- Inhalt
- The amount of data, generated in the pursuit of scientific discovery, keeps rapidly increasing across all major scientific disciplines. How can we make sense of large, time-dependent, high-dimensional and multi-variate data? This lecture provides an introduction into scientific visualization. Throughout the course, we cover the fundamental perception basics needed to convey information accurately. After categorizing different data types based on their dimensionality, we dive deeper into specific techniques for scalar and vector valued data. To facilitate the discovery of patterns and to support the communication of findings, we further elaborate on data reduction, feature extraction, and interactive exploration.
The lecture covers the following topics:
a review of scalar and vector calculus
data structures and data acquisition techniques
direct and indirect scalar field visualization
geometry-based, feature-based and topology-based vector field visualization
multi-variate data visualization
- ECTS-Informationen:
- Title:
- Applied Visualization
- Credits: 5,0
- Prerequisites
- The lecture is given in English.
- Zusätzliche Informationen
- Erwartete Teilnehmerzahl: 120, Maximale Teilnehmerzahl: 120
- Zugeordnete Lehrveranstaltungen
- UE: Tutorials to Applied Visualization
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Dozentinnen/Dozenten: Prof. Dr.-Ing. Tobias Günther, M.Sc Xingze Tian, M.Sc. Franziska Kranz
Zeit und Ort: Do 14:15 - 15:45, 16:15 - 17:45, Zoom-Meeting
- Verwendung in folgenden UnivIS-Modulen
- Startsemester SS 2021:
- Applied Visualization (AppVis)
- Institution: Lehrstuhl für Informatik 9 (Graphische Datenverarbeitung)
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