183.588 Seminar in Computer Vision and Pattern Recognition
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2022W, SE, 2.0h, 3.0EC
TUWELLectureTubeQuinn ECTS survey


  • Semester hours: 2.0
  • Credits: 3.0
  • Type: SE Seminar
  • LectureTube course
  • Format: Presence

Learning outcomes

After successful completion of the course, students are able to...

  • to write structured, scientific texts
  • to find relevant literature on a specific topic
  • to name and distinguish the different types of scientific communication (conferences, journals, etc.)
  •  to summarise scientific findings in a short presentation (5 or 10 minutes) and to apply learned presentation techniques

Subject of course

The purpose of this course is to help students to communicate ideas better and to learn the skills of scientific communication. The main aims are: o to improve communication skills o to concentrate on scientific communication, both written and oral o to learn about how scientific communication is performed at workshops, conferences, and in journals. Further goals include training graduate and PhD students how to access information about different topics, such as research results, conferences, etc., in paper-based publications and on the WWW to write cv's, abstracts, extended abstracts, and articles for acceptance at international conferences and publications (both with regard to language and contents) to review and assess submissions to scientific conferences.

Teaching methods

Writing exercises (dealing with content as well as language) will include the students  abstracts, extended abstracts, and papers. Presentation exercises include a 5 minutes and 10 minutes talk about a chosen topic. Presentations will be video-recorded and made available to students for self-assessment.

Mode of examination


Additional information

ECTS Breakdown: 3 ECTS = 75h

14h    Seminar
10h    Literature research and selection of papers
2h      Writing of Informative Abstract
17h    Writing of Extended Abstract
8h      Preparation of 1st presentation
17h    Writing of final seminar paper
7h      Preparation of 2nd presentation

Please consider the plagiarism guidelines of TU Wien when writing your seminar paper: Directive concerning the handling of plagiarism (PDF)



Course dates

Tue13:00 - 17:0025.10.2022 - 24.01.2023Seminarraum FAV 01 A (Seminarraum 183/2) Seminar
Seminar in Computer Vision and Pattern Recognition - Single appointments
Tue25.10.202213:00 - 17:00Seminarraum FAV 01 A (Seminarraum 183/2) Seminar
Tue08.11.202213:00 - 17:00Seminarraum FAV 01 A (Seminarraum 183/2) Seminar
Tue22.11.202213:00 - 17:00Seminarraum FAV 01 A (Seminarraum 183/2) Seminar
Tue29.11.202213:00 - 17:00Seminarraum FAV 01 A (Seminarraum 183/2) Seminar
Tue06.12.202213:00 - 17:00Seminarraum FAV 01 A (Seminarraum 183/2) Seminar
Tue13.12.202213:00 - 17:00Seminarraum FAV 01 A (Seminarraum 183/2) Seminar
Tue20.12.202213:00 - 17:00Seminarraum FAV 01 A (Seminarraum 183/2) Seminar
Tue10.01.202313:00 - 17:00Seminarraum FAV 01 A (Seminarraum 183/2) Seminar
Tue17.01.202313:00 - 17:00Seminarraum FAV 01 A (Seminarraum 183/2) Seminar
Tue24.01.202313:00 - 17:00Seminarraum FAV 01 A (Seminarraum 183/2) Seminar

Examination modalities

Written exercises (Abstract, Extended Abstract and Paper) will be evaluated and corrected by the lecturers with grades. The presentations will also be graded and discussed with oral feedback. For a detailed schedule of the course, refer to the homepage of the course.

Course registration

Begin End Deregistration end
01.09.2022 12:00 24.10.2022 09:00 24.10.2022 12:00


Study CodeObligationSemesterPrecon.Info
066 932 Visual Computing Mandatory2. Semester
066 935 Media and Human-Centered Computing Mandatory elective
066 936 Medical Informatics Mandatory elective


No lecture notes are available.

Previous knowledge

This seminary is intended as preparation for the presentation of the own scientific work within master- or PhD thesis defense or on conferences and workshops. Therefore deeper knowledge of the area of study is expected.