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[ INMAWKVDBVA ] KV (*)Digital Image Processing

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(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload Ausbildungslevel Studienfachbereich VerantwortlicheR Semesterstunden Anbietende Uni
3 ECTS M1 - Master 1. Jahr Informatik Josef Scharinger 2 SSt Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum Masterstudium Computer Science 2022W
Ziele (*)Students understand the principles of processing, analysis, compression and protection of digital images.
Lehrinhalte (*)Concept and generation of digital images, discrete transforms for digital images, restoration of images, geometric operations on digital images, digital image enhancement,segmentation of images, feature extraction from images, classification of objects in images, image recognition using convolutional neural networks (CNNs), object detection and segmentation using R-CNNs, semantic segmentation using FCNs, JPEG-standards for image compression, digital watermarking.

Project: students have to choose, analyze, and document (in groups) a practical digital image processing system.

Beurteilungskriterien (*)Written exam at the end of the semester; realization, presentation and documentation of (small) practical project.
Lehrmethoden (*)Slide presentation with case studies on the blackboard; project
Abhaltungssprache Deutsch
Literatur (*)PDF-versions of the slides used in the lecture will be made available via KUSSS.

Recommended reading:

  • Klaus D. Tönnies (2005). Grundlagender Bildverarbeitung. Person Studium.
Lehrinhalte wechselnd? Nein
Sonstige Informationen (*)https://www.jku.at/institut-fuer-computational-perception/lehre/alle-lehrveranstaltungen/digitale-bildverarbeitung/
Präsenzlehrveranstaltung
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