M.Sc. Applied Image and Signal Processing

  • On Campus
  • 24 months
  • EUR363 per Semester (EEA

    European Economic Area tuition fee is applicable to the students from EU countries, Iceland, Liechtenstein, Norway and Switzerland.

    )
  • English ( Take IELTS test or Find a course )
| Salzburg, Austria
Graduates of the two-year Joint Master Program "Applied Image and Signal Processing" (offered at Salzburg University of Applied Sciences) understand and develop signal and image processing at the highest level and make use of it. Every year, this international program offers 20 study places to ambitious students from IT and mathematics related Bachelor programs.

Description

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Graduates of the two-year Joint Master Program "Applied Image and Signal Processing" (offered at Salzburg University of Applied Sciences) understand and develop signal and image processing at the highest level and make use of it. Every year, this international program offers 20 study places to ambitious students from IT and mathematics related Bachelor programs.

Imagine the possibilities ...

Image and signal processing affect our daily lives in an ever-increasing way. Participate in designing this fascinating technology and shape ITs future function in business and society.

Todays networked image and signal generating devices provide a historically unmatched volume of raw data for automated decision making and control systems. The expectations are high: how can we design new tools and software in order to best distil useful information.

A lot of interesting research and development projects in the private and the public sectors are calling for your expertise. Alternatively, this degree will open career tracks in Universities and research centers.

Detailed Course Facts

Application deadline Non-EU:March 31; EU:Sep1st
Tuition fee
  • EUR726 per semester ( Non-EEA

    )
  • EUR363 per semester ( EEA

    European Economic Area tuition fee is applicable to the students from EU countries, Iceland, Liechtenstein, Norway and Switzerland.

    )

tuition fee at least € 363,- per semester (up to double amount for NON-EU countries) + € 18.70 student union fee per semester

Start date
Credits (ECTS) 120 ECTS
Duration full-time 24 months
Partnership Joint
Delivery mode On Campus
Educational variant Full-time

Course Content

1. Semester

  • Digital Signal Processing
  • Hardware Oriented Signal Processing
  • Signals and Systems
  • Selected Topics in Mathematics and Modelling
  • Digital Signal Processing

2. Semester

  • Digital Signal Processing
  • Signals and Systems
  • Applied Statistics
  • Digital Signal Processing

3. Semester

  • IT-Projectmanagement and Softwareprojects
  • Master Seminar
  • Data Mining
  • Pattern Recognition
  • Selected Topics in Applied Image and Signal Processing
  • Medical Imaging
  • Selected Topics in Applied Image and Signal Processing
  • Selected Topics in Hardware Oriented Signal Processing

4. Semester

  • Master Thesis
  • Master Seminar
  • Master Exam

English Language Requirements

Take IELTS test

Requirements

Completion of a relevant Bachelor's programme in the field of informatics or mathematics or another technical degree programme at a recognized Austrian or foreign post-secondary institution. To be considered relevant, the completed programme has to meet the following criteria:

The programme compromises at least 180 ECTS credit points (corresponds to three academic years) including:

  • core area informatics by a minimum number of 18 ECTS credit points or semester-long courses of at least 12 contact hours per week (e.g. high level programming language, object oriented programming, procedural programming languages, algorithms and data structures, Mathematica/Matlab)

  • core area mathematics by a minimum number of 12 ECTS credit points or semester-long courses of at least 9 contact hours per week (e.g. foundations of calculus / analysis and linear algebra).

Adequate English proficiency is assumed, ideally (but not necessarily) documented through a certificate (e.g. TOEFL) and will be assessed in an individual interview.

Work Experience

No work experience is required.

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