Course

DLO - image processing master

PDF Course Catalog Deutsche Version: DLO

Version: 1 | Last Change: 28.10.2019 15:21 | Draft: 0 | Status: vom verantwortlichen Dozent freigegeben

Long name image processing master
Approving CModule DLO_MaET, DLO_MaMT, DLO_MaTIN
Responsible
Prof. Dr. Jan Salmen
Professor Fakultät IME
Level Master
Semester in the year summer semester
Duration Semester
Hours in self-study 60
ECTS 5
Professors
Prof. Dr. Jan Salmen
Professor Fakultät IME
Requirements The students should have some basic knowledge about image processing and pattern recognition
Language German
Separate final exam Yes
Literature
Final exam
Details
project documentation
Minimum standard
The documentation has to contain a description of the applied method and the achieved results. Principles of scientific work have to be applied. The used programs must run without errors, and the results must be plausible.
Exam Type
project documentation

Learning goals
Knowledge
Deep learning algorithms and their application for object recognition in images.
learneing algorithms, their training and evaluation
Expenditure classroom teaching
Type Attendance (h/Wk.)
Lecture 2
Tutorial (voluntary) 0
Special literature
keine/none
Special requirements
keine
Accompanying material
keine/none
Separate exam
none

Learning goals
Skills
training of a neural network
evaluation of the performance of a neural network
Expenditure classroom teaching
Type Attendance (h/Wk.)
Practical training 3
Tutorial (voluntary) 0
Special literature
keine/none
Special requirements
keine
Accompanying material
keine/none
Separate exam
Exam Type
solving exercises within limited functional / methodical scope
Details
Training and evaluation of a neural network with dedicated examples
Minimum standard
Presence and active colaboration

Learning goals
Knowledge
reading of selected literature
Skills
in-depth implementation and evaluation of selected image processing method
document results in an adequate way
implement algorithim from literature
assessment of results
Expenditure classroom teaching
Type Attendance (h/Wk.)
Project 0
Tutorial (voluntary) 0
Special literature
keine/none
Special requirements

Accompanying material
elektronische Version der verwendeten Literatur
Separate exam
none

Impressum
Datenschutzhinweis
Haftungshinweis
Bei Fehlern, bitte Mitteilung an die
Webredaktion der Fakultät IME

© 2022 Technische Hochschule Köln