Master of Computer Science - Visual Computing and Communication (VCC)
The Visual Computing and Communication (VCC) program is a part of the Master of Computer Science at Sorbonne University. It focuses on computer vision and computer communication across a broad spectrum of subjects (image acquisition and processing, image analysis, compression and transmission of images, computer graphics, learning and decision-making, content delivery networking, network applications, cloud computing, and wireless nertworks.)
Students undertaking the VCC program will acquire theoretical skills as well as the ability to analyze and discuss scientific papers, choose and implement appropriate methods to solve concrete problems related to images and networks, perform oral presentations and write scientific reports. They will also learn to work both independently and in a team, identify and seek appropriate resources for advancing their work, and take initiatives.
During the second year, the students will choose between "Advanced Image Understanding" or "Smart Mobility Systems".
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.
How much does it cost: Tuition fees for the academic year 2020/21 (should be similar in 2021/2022)
- For French and European students (nationals of a member country of the European Union, the European Economic Area, Andorra or Switzerland), students who are residents of Quebec or international students who hold a long-term residence card : Tuition charges will be €243 per year.
- For non EU-students, you will be required to pay differentiated registration fees. The total registration fee that you will be required to pay will be €3,770 per year. In recent years, Sorbonne Université has compensated for the differentiated cost but this has not yet been decided for the next academic year.
- No tuition fees, whether differentiated or not for…
- Students who come to study in France as part of a partnership agreement between universities that provides for total exemption from enrolment fees (like the Erasmus+ exchange programme in particular)
- Students who have been awarded a French government grant (BGF)
- Students who have been awarded a grant from their host institution, providing for total exemption from enrolment fees.
- Partial or total exemption for Non-EU students who have been granted full or partial exemption from tuition fees by their host institution in France or by the French embassy in their home country.
When and where to apply:
- French and European students (nationals of a member country of the European Union, the European Economic Area, Andorra or Switzerland), students who are residents of Quebec or international students who hold a long-term residence card have to apply from mid April to end of June on the Sorbonne Université web site (the link will be provided later).
- Foreign students residing in one of the following 46 countries (Algeria, Argentina, Benin, Brazil, Burkina Faso, Burundi, Cameroon, Chile, China, Colombia, Comoros, the Republic of the Congo, Democratic Republic of Congo, Djibouti, Egypt, Gabon, Guinea, Haïti, India, Indonesia, Iran, Ivory Coast, Japan, Kuwait, Lebanon, Madagascar, Mali, Morocco, Mauritius, Mauritania, Mexico, Niger, Nigeria, Peru, Russia, Saudi Arabia, Senegal, Singapore, South Korea, Taiwan, Tchad, Togo, Tunisia, Turkey, United Kingdom, United States of America, and Vietnam) have to apply on the "Etudes en France" (Studying in France) web site from November to March (check on your local delegation). Please select “Sorbonne Université” > "Sciences et Ingénierie" > “Taught in English” > “Master indifférencié” > “DIGIT: EIT Digital - Visual Computing and Communication (VCC)” even if VCC is not anymore an EIT program.
Semester 1 (30 ECTS)
- 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.
- MU4INX51 - MODEL - 6 ECTS. Mathematical algorithms play a central role in many fields of computing, whether it is to secure the transmission and / or exchange of data (by cryptography), to analyze large masses of data, or to optimize criteria under possible constraints. The underlying algorithms share paradigms and computational schemes pertaining to algebra and mathematical analysis. Also, the concepts of complexity (binary or arithmetic), and digital conditioning hold an essential place.
- MU4INX10 - Network Programming - 3 ECTS. The objectives of teaching network programming are to know how to write simple programs, in relation to computer networks; approach the various usual tasks in a professional environment and understand the underlying mechanisms; and finally know how to effectively use high level libraries.
- FLE - French as a Foreign language - 3 ECTS.
Semester 2 (30 ECTS)
- 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.
- 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++.
- MU4INX30 - Cloud Computing - 6 ECTS. Introduction to cloud computing principal, IaaS (Infrastructure as a Service), PaaS (Plateform as a Service), and Saas (Software as a Service), cloud computing architectures, cloud providers, etc. Classical Distributed Algorithms applied to Clouds: Logical Time in distributed systems (logical clocks); Resource allocation and mutual exclusion; Broadcast protocols, membership, and synchronous view. Failures and fault tolerance: Unreliable Failure Detectors; Checkpoint and global state in distributed systems. Introduction to MPI and implementation of the above distributed algorithms in MPI. Courses with practical experiments: Virtualisation (Virtual machines and containers); Amazon Cloud (Concepts and deployment); Open Stack free open source (Deployment of Cloud Computing Service Infrastructure); Map Reduce (Programming model and an associated implementation).
- MU4INX21 - System Design and Modeling - 6 ECTS. The objective of this course is to introduce students to the problem of modeling and performance evaluation of systems. It aims at answering the following questions: Why models are important? When do we need to evaluate the performance of a system? How? What kinds of models and techniques are useful?
- 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.
Semester 1 (30 ECTS)
- 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.
- 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.
Semester 2 (30 ECTS)
- 5-6 month internship
Semester 1 (30 ECTS)
Elective courses (30 ECTS)
- MU5IN063 - Autonomic Networks - 6 ECTS. 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.
- MU5IN050 - Cellular Networks - 6 ECTS. This course presents network architecture and protocols of 2G-GSM, 3G-UMTS, 4G-LTE networks and the upcoming 5G technologies such as C-RAN, Mobile Edge Computing, SDN-NFV and network slicing. The course explains problems in both access network and core network of a mobile network operator and provides basic techniques for performance analysis, resource allocation, network dimensioning and optimization.
- MU5IN64 - Methodology for research in networking - 6 ECTS.The objective of this course is to help students improve fundamental skills when conducting research in computer networking: critical reading, writing scientific papers, data analysis, and oral presentation.
- MU5IN062 - Network analysis and mining - 6 ECTS. Network Analysis and Mining is a course at the crossroad between data mining and graph algorithmic. We present concepts and tools for the analysis of real networks represented as graphs, such as online social networks, communication networks, the web, etc. Among the topics addressed in this course : measurement and dynamics of the Internet, community detection in social networks, research and filtering of information on the web.
- MU5IN076 - Network data analysis - 6 ECTS. Introduction to probability and statistics. Bayes's law. Data collection, parameter estimation and regression methods. Statistical fitting. Hypothesis testing and applications to identification of changes that influence the network operation. Clustering and classification. Time-series analysis.
- MU5IN066 - Internet Measurement - 6 ECTS. This course presents the measures that can be performed in local networks, access networks and transit networks. It discusses which measures can be performed in the network, transport and application layers, or MAC. The student will learn to perform measurements using active measurement tools and passive measures, with practical exercises deployed on large experimental platforms.
- MU5IN056 - Network Evolution with Virtualization and Automation - 6 ECTS. The goal of this course is to present new technologies designed for advanced operations of IP networks in the last twenty years. The course starts with the evolution of IP switching and routing architectures, with a particular focus in traffic engineering and quality-of-service architectures. Then, the evolution of the Ethernet architecture and layer-2 protocols in general is presented, showing the extensions applied to let layer-2 protocols scale going from the local area to metropolitan and data-center network segments. The course shows how IP and Ethernet evolution recently converged on novels softwarized network environments, making use of data-plane programmability, network virtualization, cloud-native systems and automation frameworks.
Semester 2 (30 ECTS)
- 5-6 month internship