Master in Image Processing and Computer Vision (IPCV)

General

Program Description

This international Master's program covers a wide range of methods used in image processing and computer vision.

Program factsheet

  • Academic cooperation: Pazmany Peter Catholic University (Budapest, Hungary), Universidad Autónoma de Madrid (Spain), University of Bordeaux (France).
  • Admission requirements:
    • Hold a Bachelor's degree or equivalent in engineering science, mathematics, computer science or signal processing before the start of the program.
    • An average grade of at least “Good” according to local criteria for the courses completed before the mobility period.
    • Adequate knowledge of written and spoken English, equivalent to B2 according to the CEFR B2 or IELTS score of 6.5 or TOEFL of 90. Native English speakers do not have to submit English test results.
  • Program duration: 2 years (120 ECTS).
  • Language requirements: English (equivalent to B2 according to the CEFR).
  • Tuition fees:
    • Self-funded program country students: 4,500 € per year (9,000€ for the 2-year program)
    • Self-funded partner country students: 9,000€ per year (18,000€ for the 2-year program)
  • Level: Fully recognized triple Master's Degree, completed by three diploma supplements.
    • Pazmany Peter Catholic University (PPCU): MSc degree in Engineering Information Technology; specialization in IPCV.
    • Universidad Autónoma de Madrid (UAM): Master's degree in ICT Research and Innovation (i2-ICT).
    • University of Bordeaux (UBx): Master's degree in "Informatique" (Computer Science); specialization in IPCV.
    • A diploma supplement is additionally delivered by each university.

Program outline

The International Master Program in Image Processing and Computer Vision, managed by the University of Bordeaux, provides specialized training in a field of increasing importance in our daily lives. It is essential in domains such as medicine, surveillance, industrial control, remote sensing, e-commerce, and automation. The program covers a wide range of methods in computer vision, guaranteeing highly-qualified graduates in this field.

Three partner universities, with internationally recognized experience in these domains, have pooled their complementary expertise and developed this international postgraduate cooperation initiative.

123119_photo-1555949963-ff9fe0c870eb.jpg Shahadat Shemul / Unsplash

Program structure

All students follow a common mobility scheme and curriculum. Each semester is awarded 30 ECTS. Students may choose two specialization tracks:

  • Track 1: Vision and applications
  • Track 2: Vision and devices

Semester 1 to 4: content

1st semester: Pazmany Peter Catholic University

Fundamental and theoretical knowledge in mathematics, electronic computing, signal and image processing, sensors and parallel computing.

2nd semester: Universidad Autónoma de Madrid

Video analysis, medical image processing, and analysis, biometrics, computer vision for surveillance problems and initiation to research.

3rd semester: University of Bordeaux

Object-programming, deep learning, image reconstruction, variational modeling, project-management

4th semester: Training period

The last semester is dedicated to an internship at a company or research laboratory anywhere in the world.

Strengths of this Master's program?

  • The international program taught by experts from three different universities in Europe.
  • Triple Master degree.
  • International mobility period in three countries.
Last updated Oct 2019

About the School

The University of Bordeaux was newly established in 2014 following the merger of three universities. Ranked among the top universities in France for the quality of its academic courses and research, i ... Read More

The University of Bordeaux was newly established in 2014 following the merger of three universities. Ranked among the top universities in France for the quality of its academic courses and research, it was awarded the “Initiative of Excellence” by the French government in 2011. Read less
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