Communication and Media Engineering

Application
EMI Department

Module Guide

←  Back 

Interactive Distributed Applications

Teaching methods Lecture/Lab
Learning target / Competences

Target skills:
The student will gain an overview on established and modern image processing techniques. The course provides tools, methods, models and techniques for the following topics: image formation, optics, imagers, color, image segmentation, image analysis, image features, image alignment, estimation in computer vision, programming and deep learning.
 
Competences:
The student will understand basic problems in image processing and machine vision, e.g. image segmentation, feature detection, image matching or estimation problems in alignment.
He/she will know methods, algorithms and common techniques to solve the above mentioned problems. The student will be able to computationally apply the methods on
given low-level and higher-level image processing tasks in real world computer vision problems.
Duration 1
Hours per week 5.0
Overview
Classes 60 h
Individual / Group work: 60 h
Workload 120 h
ECTS 5.0
Requirements for awarding credit points

Computer Vision with Lab
Written exam K60+Lab
Das unbenotete Labor ist Voraussetzung für die Zulassung zur Klausur K60.
Credits and grades

4 CP, grades 1 ... 5
Responsible person

Prof. Dr. Rüdebusch
Frequency Every 2nd sem.
Usability

Master's degree program CME, EIM and MMR
Lectures

Interactive Distributed Applications

Type Lecture
Nr. M400
Hours per week 4.0

Interactive Distributed Applications Lab

Type Lab
Nr. M406
Hours per week 1.0
←  Back