VU Computer Vision Timetable The lecture will again be held virtually in WS2021/2022 due to the current COVID19 developments. Enclosed you will find a schedule for orientation in the self-study of the lecture part. It is advisable to follow this schedule in order to acquire the necessary theoretical knowledge for the exercise part of this … Continue reading Zeitplan
Date: TU 16:00 – 18:00, FR 10:00 – 12:00, starts 7.10.21 online see Schedule! Place: online, follow the course on TUWEL, therefore please register in TISS! Lecture: Computer Vision for Cultural Heritage Preservation Aim of course The lecture is intended for computer science students to get an insight into cultural heritage preservation and management techniques. … Continue reading Computer Vision for Cultural Heritage Preservation (VO)
When: Wed 10.00 – 12.00 c.t. Where: Lab and online Course description This course encourages students to select and implement a computer vision project of their choice. Students are free to develop in any programming language they like and to use any publicly available library they want. The only requirement is that the effort for … Continue reading Computer Vision Systems Programming (UE)
When: Wed 10.00 – 12.00 c.t. (check for updates) Where: Seminarroom (?) / ONLINE News Next deadline/task: 13. Oct .2021: 1st meeting; overview and introduction, Lab tasks, Q & A Course description Computer vision from an applied point of view. We will review popular programming languages as well as open and closed source software (e.g. … Continue reading Computer Vision Systems Programming (VO)
Termin: Dienstag 13:00 – 15:00, teilweise 13:00 – 17:00 Ort: Virtual – Zoom (Permanent Zoom Link provided via the TUWEL course) Thema im WS 21/22: Automatische Dokumentanalyse Der 2. Teil des Seminars “Wissenschaftliches Arbeiten” wird am CVL von Prof. Robert Sablatnig gemeinsam mit Marco Peer im Wintersemester abgehalten. Es dient primär als Einführung in die wissenschaftliche … Continue reading Wissenschaftliches Arbeiten (SE)
Date: Mon. 13:00 c.t. Place: Zoom / TUWEL This excursion with lecture is an elective course in the Module Applications of Computer Vision and Pattern Recognition in the Visual Computing Master The elective course “Applications of Computer Vision” is a 2h lecture/ excursion combination and is held in winter terms by Robert Sablatnig and Matthias … Continue reading Applications of Computer Vision (EX)
Dates Up to further notice, Computer Vision (VU) will be held again virtually in WS2021/2022. A timetable for orientation in the self-study of the lecture part is provided here. It is advisable to follow this schedule in order to acquire the necessary theoretical knowledge for the exercise part of this course in time. Lecture recordings … Continue reading Computer Vision (VU)
Course This seminar is given in English by Robert Sablatnig and Marco Peer in winter term. Motivation for the Course Communication, both written and oral, is crucial in most graduate jobs, whether in the commercial or the scientific sector. The successful presentation of one’s own work depends on well-developed communication skills. In the more specific … Continue reading Seminar aus Computer Vision und Mustererkennung (SE)
Supervisor: Michael Reiter (CVL), Manfred Lehner (CCRI) Praktikum mit Möglichkeit zur Fortführung im Rahmen einer Diplomarbeit in Zusammenarbeit mit dem Christian Doppler Laborator für CAR-T-Zellen der nächsten Generation Dieses CD Labor an der St. Anna Kinderkrebsforschung arbeitet an molekularen Werkzeugen zur Verbesserung der sogenannten CAR-T-Zell-Therapie, einer Krebstherapie, welche auf der Verabreichung von genetisch veränderten Immunzellen beruht. … Continue reading Verbesserung der CAR-T-Zellen Therapie durch Datenanalyse
Course description This lecture covers Deep Learning for automatic image and video analysis, such as classifying images into categories or detecting and distinguishing persons. Deep Learning has lead to breakthroughs in these fields; in certain problems, the performance of current methods based on this technology is similar or even better than that of humans – … Continue reading Deep Learning for Visual Computing