188.498 Similarity Modeling 2
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2018W, VU, 2.0h, 3.0EC, to be held in blocked form

Properties

  • Semester hours: 2.0
  • Credits: 3.0
  • Type: VU Lecture and Exercise

Aim of course

Computational media understanding with deep learning, classic machine intelligence and clustering.

Subject of course

  • Low-level feature extraction from audiovisual media
  • Semantic feature modeling
  • Similarity modeling and feature classifciation
  • Performance evaluation and statistical data analysis
  • Examples of applications and advanced topics

Additional information

Pedagogic concept

  • Frame of knowledge transfer with lecture block at the beginning an exam at the end of the lecture
  • Exploration of lecture contents in a lab project in groups of 2-3 students
  • Application of state of the art visualization and seminar methods for enabling student participation during the lecture
  • Application of an open forum for knowledge exchange over groups during the lab course

ECTS Breakdown

Description                       ECTS  Hours
---------------------------------------------
Preparation                       0.04    1.0
Lecture                           0.32    8.0
Preparation of the Group Project  0.04    1.0
Group Project Work                1.88   47.0
Preparation of the Oral Exam      0.70   17.5
Oral Exam                         0.02    0.5
---------------------------------------------
Total                             3.00   75.0

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Thu09:00 - 10:0004.10.2018 Seminar Room 1882, Favoritenstr 9, Stair 3, 4th Floor, green AreaPre-Lecture Meeting
Thu13:00 - 16:0018.10.2018FAV Hörsaal 3 Zemanek (Seminarraum Zemanek) Lecture
Fri09:00 - 12:0019.10.2018FAV Hörsaal 3 Zemanek (Seminarraum Zemanek) Lecture
Course is held blocked

Examination modalities

Oral exam on lecture contents + lab project

Course registration

Begin End Deregistration end
14.09.2018 00:00 18.10.2018 16:00 18.10.2018 16:00

Curricula

Study CodeObligationSemesterPrecon.Info
066 645 Data Science Not specified
066 926 Business Informatics Not specified
066 931 Logic and Computation Mandatory elective
066 932 Visual Computing Mandatory elective
066 935 Media and Human-Centered Computing Mandatory elective
066 936 Medical Informatics Mandatory elective

Literature

H. Eidenberger: "Professional Media Understanding", Atpress, Vienna, 2012.

List of topics and links in the TUWEL forum.

Previous knowledge

Programming in Java and/or Python

Preceding courses

Continuative courses

Miscellaneous

Language

English