183.663 Deep Learning for Visual Computing
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2022S, VU, 2.0h, 3.0EC
TUWEL

Properties

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

Learning outcomes

After successful completion of the course, students are able to develop and apply deep learning methods for automatic image analysis (e.g. for classification of images or detection of people in images). 

 

Subject of course

Deep learning for automatic image analysis:

* Brief recap of Computer Vision and Image Processing
* Machine Learning: overview, parametric models, iterative optimization
* Feedforward Neural Networks, backpropagation
* Convolutional Neural Networks for classification, detection, and segmentation
* Generative models for image synthesis
* Software libraries and practical aspects
* Preprocessing, data augmentation, regularization, visualizations
* Guest lectures on medical applications and ethical aspects

The contents presented in the lecture will be applied in exercises.

 

Teaching methods

Lecture and individual programming tasks in groups of two.

Mode of examination

Written

Additional information

ECTS breakdown: 3 ECTS = 75h

16h lecture
34h programming exercises
24h exam preparations
1h exam
---
75h

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Wed13:00 - 14:0002.03.2022Hörsaal 15 Introduction
Wed12:00 - 14:0009.03.2022 - 29.06.2022Hörsaal 15 Lecture
Deep Learning for Visual Computing - Single appointments
DayDateTimeLocationDescription
Wed02.03.202213:00 - 14:00Hörsaal 15 Introduction
Wed09.03.202212:00 - 14:00Hörsaal 15 Lecture
Wed16.03.202212:00 - 14:00Hörsaal 15 Lecture
Wed23.03.202212:00 - 14:00Hörsaal 15 Lecture
Wed30.03.202212:00 - 14:00Hörsaal 15 Lecture
Wed06.04.202212:00 - 14:00Hörsaal 15 Lecture
Wed27.04.202212:00 - 14:00Hörsaal 15 Lecture
Wed04.05.202212:00 - 14:00Hörsaal 15 Lecture
Wed11.05.202212:00 - 14:00Hörsaal 15 Lecture
Wed18.05.202212:00 - 14:00Hörsaal 15 Lecture
Wed25.05.202212:00 - 14:00Hörsaal 15 Lecture
Wed01.06.202212:00 - 14:00Hörsaal 15 Lecture
Wed08.06.202212:00 - 14:00Hörsaal 15 Lecture
Wed15.06.202212:00 - 14:00Hörsaal 15 Lecture
Wed22.06.202212:00 - 14:00Hörsaal 15 Lecture
Wed29.06.202212:00 - 14:00Hörsaal 15 Lecture

Examination modalities

Written exam (50%) and compulsory programming exercises (50%).

Exams

DayTimeDateRoomMode of examinationApplication timeApplication modeExam
Mon14:00 - 16:0031.10.2022EI 1 Petritsch HS written27.09.2022 08:00 - 28.10.2022 23:00TISSExam

Course registration

Begin End Deregistration end
11.02.2022 14:00 02.03.2022 23:00 04.03.2022 23:00

Precondition

The student has to be enrolled for at least one of the studies listed below

Group Registration

GroupRegistration FromTo
Group 109.03.2022 13:0016.03.2022 12:00
Group 209.03.2022 13:0016.03.2022 12:00
Group 309.03.2022 13:0016.03.2022 12:00
Group 409.03.2022 13:0016.03.2022 12:00
Group 509.03.2022 13:0016.03.2022 12:00
Group 609.03.2022 13:0016.03.2022 12:00
Group 709.03.2022 13:0016.03.2022 12:00
Group 809.03.2022 13:0016.03.2022 12:00
Group 909.03.2022 13:0016.03.2022 12:00
Group 1009.03.2022 13:0016.03.2022 12:00
Group 1109.03.2022 13:0016.03.2022 12:00
Group 1209.03.2022 13:0016.03.2022 12:00
Group 1309.03.2022 13:0016.03.2022 12:00
Group 1409.03.2022 13:0016.03.2022 12:00
Group 1509.03.2022 13:0016.03.2022 12:00
Group 1609.03.2022 13:0016.03.2022 12:00
Group 1709.03.2022 13:0016.03.2022 12:00
Group 1809.03.2022 13:0016.03.2022 12:00
Group 1909.03.2022 13:0016.03.2022 12:00
Group 2009.03.2022 13:0016.03.2022 12:00
Group 2109.03.2022 13:0016.03.2022 12:00
Group 2209.03.2022 13:0016.03.2022 12:00
Group 2309.03.2022 13:0016.03.2022 12:00
Group 2409.03.2022 13:0016.03.2022 12:00
Group 2509.03.2022 13:0016.03.2022 12:00
Group 2609.03.2022 13:0016.03.2022 12:00
Group 2709.03.2022 13:0016.03.2022 12:00

Curricula

Literature

Preceding courses

Miscellaneous

Language

English