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Artificial Intelligence in Image & Signal Processing*
University | Course | SWS | ECTS | TYPE |
---|---|---|---|---|
PLUS | Image Processing and Imaging | 2 | 2 | VO |
PLUS | Image Processing and Imaging | 1 | 2 | PS |
PLUS | Imaging Beyond Consumer Cameras | 2 | 2 | VO |
PLUS | Imaging Beyond Consumer Cameras | 1 | 2 | PS |
SUAS | Mathematics & Modelling | 4 | 5 | IL |
SUAS | Digital Signal Processing 1 | 3 | 5 | IL |
SUAS | Data Science | 3 | 5 | IL |
SUAS | Analytics & Knowledge Discovery | 2 | 3 | IL |
PLUS | Natural Computation | 2 | 2 | VO |
PLUS | Natural Computation | 1 | 2 | PS |
Total | 21 | 30 |
University | Course | SWS | ECTS | TYPE |
---|---|---|---|---|
PLUS | Fourier Analysis, Filter Banks & Wavelets | 3 | 4 | VO |
PLUS | Fourier Analysis, Filter Banks & Wavelets | 2 | 3 | PS |
SUAS | Applied Statistics | 3 | 4 | IL |
SUAS | Digital Signal Processing 2 | 3 | 5 | IL |
SUAS | Machine Learning | 3 | 5 | IL |
PLUS | Audio Processing | 2 | 3 | VO |
PLUS | Audio Processing | 1 | 2 | PS |
PLUS | Media Data Formats | 2 | 2 | VO |
PLUS | Media Data Formats | 1 | 2 | PS |
Total | 20 | 30 |
University | Course | SWS | ECTS | TYPE |
---|---|---|---|---|
PLUS | Computer Vision | 2 | 3 | VO |
PLUS | Computer Vision | 1 | 2 | PS |
PLUS | Geometric Modelling | 2 | 3 | VO |
PLUS | Geometric Modelling | 1 | 2 | PS |
PLUS | Master Seminar 1 | 2 | 3 | SE |
SUAS | Agile Project Management | 2 | 3 | IL |
Ethics & Sustainability | 1 | 1 | IL | |
Elective 1 | 3 | 5 | ||
Elective 2 | 3 | 5 | ||
Free Elective 1 | 2 | 3 | ||
Total | 19 | 30 |
University | Course | SWS | ECTS | TYPE |
---|---|---|---|---|
SUAS | Master Seminar 2 | 1 | 2 | SE |
SUAS | Master Thesis | 0 | 23 | IT |
SUAS | Master Exam | 0 | 2 | DP |
Free Elective 2 | 2 | 3 | ||
Total | 3 | 30 |
ELECTIVE 1
Elective 1: Natural Language Processing |
University | Course | SWS | ECTS | TYPE |
---|---|---|---|---|
SUAS | Natural Language Processing | 2 | 3 | IL |
SUAS | Applied Natural Language Processing | 1 | 2 | IL |
Total | 3 | 5 |
Elective 1: Reinforcement Learning |
University | Course | SWS | ECTS | TYPE |
---|---|---|---|---|
SUAS | Reinforcement Learning | 2 | 3 | IL |
SUAS | Applied Reinforcement Learning | 1 | 2 | IL |
Total | 3 | 5 |
ELECTIVE 2
Elective 2: Medical Imaging |
University | Course | SWS | ECTS | TYPE |
---|---|---|---|---|
PLUS | Medical Imaging | 2 | 3 | VO |
PLUS | Medical Imaging | 1 | 2 | PS |
Total | 3 | 5 |
Elective 2: Biometric Systems |
University | Course | SWS | ECTS | TYPE |
---|---|---|---|---|
PLUS | Biometric Systems | 2 | 3 | VO |
PLUS | Biometric Systems | 1 | 2 | PS |
Total | 3 | 5 | ||
Elective 2: Media Security |
University | Course | SWS | ECTS | TYPE |
---|---|---|---|---|
PLUS | Media Security | 2 | 3 | VO |
PLUS | Media Security | 1 | 2 | PS |
Total | 3 | 5 |
Elective 2: Advanced Machine Learning |
University | Course | SWS | ECTS | TYPE |
---|---|---|---|---|
PLUS | Advanced Machine Learning | 2 | 3 | VO |
PLUS | Advanced Machine Learning | 1 | 2 | PS |
Total | 3 | 5 |
*from fall 2021 onwards, new title for the master programme Applied Image and Signal Processing and curriculum; upon approval
Legend | |
SUAS | Courses will take place at the Salzburg University of Applied Sciences |
PLUS | Courses will take place at the Paris Lodron University of Salzburg |
Semester | Semesters 1, 3, 5: courses held only in winter semester (mid-September to end of January), Semesters 2, 4, 6: courses held only in summer semester (mid-February to end of June) |
SWS | weekly contact hours over 14 weeks in semester (example SWS 2 equals 28 contact hours for the whole course |
ECTS Credits | Work load in ECTS credits, 1 ECTS credit equals an estimated 25 hours of work for the student |
INTL-Code | Indicates categories for incoming students 5: offered in English on a routine basis 4: offered in English if a specified number of incoming students attend (usually 3) 3: taught in German but support material in English, exams can also be taken in English, active support from a student buddy 2: taught in German, incoming students require sufficient German proficiency to follow class 1: not available for incomings |
Type | BP = Bachelor final exam DP/MP = Master final exam IL = Lecture with integrated project work IT = Individual training/phases LB = Lab (session) PS = Pro-seminar PT = Project RC = Course with integrated reflective practice RE = Revision course SE = Seminar TU = Tutorial UB = Practice session/Subject practical sessions VO = Lecture |