Detailed Program

Mobility Scheme
Academic Calendar
Learning Outcomes

The Master programme is built upon existing curricula in information technology, engineering, applied mathematics and computer science. These four fields have been gathered together to propose an excellent and well-designed curriculum. Each semester has its own objective:

  • 1st semester: Pazmany Peter Catholic University, Budapest, Hungary (PPCU)
    The objective of the first semester is to provide all students with the same fundamental and theoretical knowledge in mathematics, electronic computing, signal and image processing, sensors and parallel computing. It ensures that students from a variety of backgrounds (some with a Bachelor in only one of these specializations) will be ready for the following semesters.
     
  • 2nd semester: Universidad Autónoma de Madrid, Spain (UAM)
    The second and third semesters are entirely focused on image processing and computer vision problems. During the second semester, students study medical image processing and analysis, biometrics, computer vision for surveillance problems, and image classification.
     
  • 3rd semester: University of Bordeaux, France (UBx)
    This final semester of study provides the students with more advanced knowledge on programming and addresses video coding, satellite image processing, and multi-dimensional imaging. Finally, a project-management class is mandatory.
     
  • 4th semester: Training period
    The last semester is dedicated to an internship at a company or research laboratory anywhere in the world.

Each semester is awarded 30 ECTS, with classes ranging from 3 to 6 ECTS. These classes can be categorized as follows:

  • Fundamentals
    This category corresponds to intensive, one-week courses (mathematics, signal processing, computer science, programming tools), scheduled at the beginning of the first semester, ensuring that students from different backgrounds gain sufficient knowledge to pursue the IPCV programme. These classes are mandatory for all students not having successfully passed an initial test. No credits are awarded.
     
  • Core classes
    This category includes all classes entirely dedicated to the field of interest.
     
  • Optional classes
    Each student will have the possibility to sign up for optional classes during the first semester. We will advise each student individually, to tailor the options to the student’s interests and previous curriculum.
     
  • Tutored research and development project
    The project begins during the second semester and ends during the third semester.
     
  • Project management
    This class introduces students to the tools commonly used by companies for handling new-technology projects.
     
  • Training period

All three partners offer students an excellent scientific environment and top-quality facilities. The entire teaching staff is made up of researchers, which ensures that the courses incorporate recent advances in the field. Furthermore, students receive individual attention from the teaching and administrative staff to help them solve any problems that may arise.

All students follow the same course curriculum except for a few optional courses in the first semester. The calendar is the same for everyone.

1st semester: PPCU, Budapest

Starts: Beginning of September
Ends:  Mid-December
Exams: Mid-December to Mid-January


2nd semester: UAM, Madrid

Starts: End of January
Ends: May
Exams: Beginning of June


3rd semester: UB, Bordeaux

Starts: Beginning of September
Ends: December
Exams: Beginning of January


4th semester: Training – any country

Starts: Mid-January
Ends: Mid-June
Defense: Beginning of July

The programme gives the students theoretical and practical knowledge allowing them to adapt to any kind of job related to image processing and computer vision. The graduates have the following skills:

  • Development, strategic planning, coordination, and technical management of projects
  • Design, implement, deploy and debug applications
  • Formulate correct opinions and reviews to make efficient decisions
  • Analyze and detect the information needs that arise in a scientific and technological environment
  • Understand and solve emerging problems and raise original ideas
  • Tackle various applications: medicine, security, privacy preservation, and social networks quality…
  • Respect scientific ethics in all circumstances
  • Ability to work in team
  • Communicate in English: prepare, discuss, write and defend for scientific and technical projects

The scientific learning outcomes can be summarized as follows:

  • Strong background in mathematics and signal processing
  • Excellent knowledge on methods in image processing and computer vision
  • Aware of the needs in the field and efficiency to provide some solutions
  • Good programming skills in C, C++, Java, Matlab

Students enrolled in the programme become rapidly aware of the needs within the field of image processing and computer vision, as well as becoming effective in providing solutions. Their skills will greatly benefit industry.

The tutored research and development projects allow students to prepare themselves for their training period. At the same time, students have the opportunity to meet with companies during each semester of the programme, thereby improving their employability and reinforcing their motivation to enter the professional world. A 3-ECTS course is also dedicated to project management, to prepare students to join or even lead groups of employees. Finally, the last semester of the curriculum is entirely dedicated to a training period in either the public or the private sector.

Thanks to their knowledge of industrial needs and the high-quality instruction they have received, our graduates will be able to:

  • Develop image- and video-related software for small and large companies.
  • Propose innovative algorithms to solve new problems arising as visual technologies continue to evolve.
  • Join and even lead project teams.
  • Continue as PhD students by joining top-level multidisciplinary research teams, either at laboratories or in companies’ research departments.
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