Warning: Use of undefined constant bleufonce - assumed 'bleufonce' (this will throw an Error in a future version of PHP) in /dsk/www-master/html/parcours/digit-vcc/head.php on line 35
Master informatique : parcours DIGIT / EITdigital MS VCC

Aller au contenu  Aller au menu Aller à la recherche

Navigation principale

accès rapides, services personnalisés


Recherche détaillée


Dominique Béréziat
Head of the VCC program at SU

courriel : master.info.digit-vcc@upmc.fr


Visual Computing and Communication at SU


Advanced Image Understanding

This page describes the implementation of the VCC (Visual Computing & Communication) program at Sorbonne Université (located in the center of Paris).

EIT Digital Master School allows students to study a first year (called entry) and second year (called exit) in two partner universities. Additional information about the structure of EIT Master school can be found here.

VCC is a part of EIT Digital Master School, and focuses on computer vision in a large spectrum (acquisition, image processing, image analysis, compression and transmission of images, network applications, computer graphics, including learning and decision-making). Moreover, a significant part of courses addresses business aspects to create products and services. Each university partner of VCC proposes an exit with a specialization:

The entry at Sorbonne University proposes, in the same way as other partner universities, basic courses on image and signal processing, computer graphics, network and entrepreneurship (see I.&E. minor for details). The exit at SU provides advanced courses in image analysis, including biomedical imaging, computer graphics. Courses are taught jointly to students of the EIT program and other students from the Master of Computer Science of Sorbonne Université.

VCC MobilityMap

The students will acquire theoretical skills, as well as the ability to analyze and discuss a scientific paper, to choose and implement appropriate methods to solve a concrete problem related to images, to give oral presentations and to write scientific reports. They will also learn to work independently as well as in a team, to identify and seek appropriate resources for advancing their work, and to take initiatives.

Who can apply: Bachelor’s holders in Computer Science, Information Technology, Mathematics, Statistics and Electrical Engineering & Electronics. Strong skills in Mathematics (probability and statistics) are required, as well as a strong background in Computer Science.

Application: see https://masterschool.eitdigital.eu/application/.

Structure of the entry (first year):

  • Semester 1 (30 ECTS):
    • Compulsory courses:
      • MU4INX41 - Fundamentals of Image Processing - 6 ECTS. This course presents fundamentals of image processing, including Fourier analysis, acquisition and theory of sampling, filtering and denoising, edge detection, segmentation. Applications are given on a few concrete problems (key-point detection, face recognition...), with practical works.
      • MU4INX06 - Signal and Communication - 6 ECTS. This course has the objective of providing the tools that are necessary for analyzing, modeling and designing digital transmission systems. The first part of the course focuses on the necessary bases in deterministic and random signal processing. The rest of the course shows their application to the physical layer of communications systems: architecture of a digital transmission chain, models and performance evaluation.
      • MU4INX05 - Computer Networking - 6 ECTS. This course focuses on core network applications requested by users and services needed at the network level. The TCP/IP architecture and all the main associated protocols are detailed with particular emphasis on multimedia applications, end-to-end control mechanisms and routing hierarchy.
      • MU4INX09 - I&E Basics - 6 ECTS. This course offers introductory lectures on technology-based entrepreneurship, marketing and markets, organization and project management, new product and process development, entrepreneurial finance, human resource development.
      • MU4INX08 - Business Development Lab 1 - 6 ECTS. This course is mainly concentrated on project work throughout the main phases of business modeling and development. It builds upon the Basic Course and will enable the student to conduct a fully‐fledged business development project. Invited entrepreneurs and practitioners hand over relevant applicable experience and knowledge in parallel to academic lectures.
  • Semester 2 (30 ECTS):
    • Compulsory courses:
      • MU4INX42 - Introduction to Computer Graphics - 6 ECTS. This course introduces the domain of 3D computer graphics, including geometric modeling and processing, image synthesis, with implementation in OpenGL and C/C++.
      • MU4INX19 - Wireless and Mobile Computing - 6 ECTS. The main objective of this course is to present how user mobility and wireless transmissions affect computer communications. The course first gives a basic understanding of the physical layer mechanisms. It presents the impact of wireless signal propagation, link budget, digital communications with an illustration based on spread spectrum technologies. It then presents a survey on existing wireless technologies with a strong emphasis on the Wi-Fi standard. Finally, this course details the impact of mobility on IP protocols, the benefits and limitations of the main proposals, as well as the constraints of data losses on existing transport protocols.
      • MU4INX91 - Project on Image Processing or Networking - 6 ECTS. Students work alone on a problem, performing a short review of the state-of-the-art and an implementation of one or several methods.
      • MU4INX22 - Business Electives - 6 ECTS. This course covers advanced topics on any of the following: business development, business finance, marketing, innovation management, intellectual property and market research.
      • MU4INX23 - Business Development Lab 2 - 3 ECTS. Second part of Business Development Lab course (see below for description).
      • MU4INX24 - ICT Innovation Summer School (summer) - 3 ECTS. This Summer School brings you together for two weeks to work in groups on business modeling and planning project in the context of a societally relevant thematic area. Summer Schools take place at different locations throughout Europe and bring together students and business partners. Summer Schools support study programs with a multidisciplinary and international dimension, and create a clear EIT Digital flavor to education.

Structure of the exit (second year)

  • Semester 1 (30 ECTS):
    • Compulsory courses:
      • MU5IN656 - Seminar and Projects - 6 ECTS. This course presents briefly a few topics not addressed in the other courses, in the form of seminars given by experts of the domain (from either the academy or the industry). It also includes a project done by the students, as an initiation to research work (critical bibliographical review, choice of a method, implementation and tests).
      • MU5IN652 - Pattern Recognition and Machine Learning for Image Understanding - 6 ECTS. This course presents theory and algorithms for classification and image understanding (Bayesian decision, machine learning, supervised and unsupervised learning, kernel-based methods, deep learning...). Illustrations are provided, on several applications for image classification. The course includes lessons and practical work.
    • Elective courses:
      • MU5IN650 - Advanced Methods for Image Analysis - 6 ECTS. This course presents advanced theories of image processing and analysis. The formalisms include continuous, discrete, algebraic, analytical and statistical approaches. The course ranges from mathematical aspects to algorithms, for pre-processing, segmentation, etc. Illustrations are provided in various domains (natural images, medical images, remote sensing images...). The course includes lessons and practical work.
      • MU5IN651 - Advanced Methods for Computer Vision - 6 ECTS. This course provides an overview of advanced techniques for computer vision, either 2D or 3D, either static or dynamic. Methods mostly aim at extracting relevant information from the observed scene. The course includes lessons and practical work.
      • MU5IN654 - Biomedical Imaging - 6 ECTS. This course presents the main acquisition techniques both in medical imaging and in biological imaging. It also details a few applications, such as registration, segmentation, shape modeling, mammography, cardiovascular imaging, biological particle tracking, etc.
      • MU5IN063 - Autonomic Networks - 6 ECTS. This course covers main scientific and technological issues of autonomous and ubiquitous networks. Principles, techniques, and examples related to the design of such networks are introduced, sometimes through similarities and differences with classical networks. Various aspects of self-* attributes are discussed, such as self-stabilization, self-configuration, self-organization, self-management, self-optimization, self-adaptiveness, etc. Passive mobility and proactive mobility are addressed and applied to sensor networks, swarms of robots, MANET, and VANET .
      • MU5IN074 - Smart Mobility Systems - 6 ECTS. This course introduces Mobile Computing: challenges and opportunities. The current state of the art (through research paper review). Mobile protocols and application design and implementation. Mobile systems design and implementation. Experimental evaluation of mobile systems.
  • Semester 2 (30 ECTS):
      • MU5INX99 - I&E Study - 6 ECTS. This course is supervised business analysis work. It focuses on applying prior I&E knowledge and competences in a real business context. This course will allow students to tackle a business challenge with a robust explorative business analysis methodology
      • 5-6 month internship - 24 ECTS