Parcours Computer Vision

Assessment Regulations

Knowledge assessment and examinations are conducted in accordance with the Common Academic Regulations, adopted on 18 December 2023 by the Board of Directors of Université Bourgogne Europe (UBE).

Examination Sessions

The assessment of knowledge is organised into two examination sessions.

First Session

The first session takes place during the teaching period (October–June).

For each teaching unit, assessment may include, in accordance with the Modalités de Contrôle des Connaissances (MCC):

• a final written examination,
• continuous assessment,
• and, where applicable, practical work assessment.

The modalities of continuous assessment, when applicable, are defined for each module by the module coordinator, in agreement with the instructors involved in the teaching unit.

In the event of a justified absence from a continuous assessment activity, the student is offered a substitute assessment whenever possible. If participation in a substitute assessment is not possible, the examination board may decide to replace the continuous assessment mark with a mark of zero.

Second Session

The second session takes place:

• in June for first-year Master’s students (M1),
• in September for second-year Master’s students (M2).

It covers the assessments of both semesters and consists of one examination per module.

In this second session, only the so-called final examination is retaken, in written or oral form. Marks obtained for practical work during the first session (when applicable), as well as continuous assessment marks, are fully retained.

The mark obtained in the second-session examination alone constitutes the final examination mark for the module in the second session.

Compensation Rules

Compensation applies:

• between course components within the same teaching unit,
• between teaching units within the same semester,
• and between semesters within the same academic year.

Repetition of a Year

Repeating a year is not automatic and is subject to a decision by the examination board.

Recognition of Student Engagement

In accordance with the Common Academic Regulations of Université Bourgogne Europe (UBE), student engagement may be formally recognised following a discussion at the very beginning of the semester with the programme coordinator, who will specify the applicable modalities.

The examination board may take this engagement into account in the form of a bonus applied to the semester average, up to a maximum of 0.2 points.

First year of the Master’s programme (M1)

Applications are submitted via https://www.vibot.org. 
This programme is offered as a full-time initial training programme.

Admission to the Second Year of the Master’s Programme (M2)

Students who have successfully completed the first year of the Master’s programme in Signal and Image Processing (TSI) or the first year of the Master’s programme in Electrical Engineering and Automatic Control (EEA) at Université Bourgogne Europe are admitted directly to the second year of the Master’s programme in Signal and Image Processing (applications managed via the eCandidat platform).

For students who do not follow this pathway (for example, holders of an equivalent first-year Master’s degree), admission is based on an application file. A pre-registration is submitted online, after which the application file must be completed with supporting documents substantiating the information provided during pre-registration and, where appropriate, supplying additional details on the applicant’s academic background. Applications are reviewed by a selection committee drawn from the teaching staff, which meets to decide on admissions.

Students holding only a foreign degree must follow the application procedure via Campus France in their country of origin.

Admission through Recognition of Prior Learning or Degree Equivalence

• Initial training: applicants should contact the academic administration responsible for the programme.
• Continuing education: applicants should contact the university’s continuing education department (phone: +33 3 80 39 51 80).

Required Documents

1. Curriculum vitae
2. Cover letter / statement of motivation
3. Most recent degree obtained and/or certificate of enrolment
4. Most recent academic transcripts
5. Proof of English language proficiency
6. Copy of a national identity card or passport
7. Birth certificate
8. Names and email addresses of two academic or professional referees

Disciplinary Skills

• Analyse and design digital image processing systems by:
  • Mastering mathematical tools and fundamental concepts in signal and image processing
  • Mastering the fundamentals of imaging physics, including light and colour
  • Mastering electronic component architectures for real-time processing
  • Mastering basic programming languages for signal processing and electronics

• Identify the role and scope of engineering sciences across all industrial sectors.
• Validate a model by comparing its predictions with experimental results and assess the limits of its validity.
• Mobilise concepts from mathematics, physics, chemistry, and thermodynamics to address problems specific to various industrial domains.
• Estimate orders of magnitude and correctly handle physical units.
• Develop and apply an accurate understanding of space and its representations.
• Implement algorithmic and programming techniques, in particular to develop basic applications for data acquisition and data processing.

Pre-professional Skills

• Position one’s role and responsibilities within an organisation in order to adapt and take initiative.
• Identify the processes involved in the production, dissemination, and valorisation of knowledge.
• Comply with principles of ethics, professional conduct, and environmental responsibility.
• Work effectively both independently and as part of a team, with responsibility for a project.
• Identify and situate professional fields potentially related to the acquired competencies, as well as the pathways leading to them.
• Characterise and promote one’s professional identity, skills, and career project according to a given context.
• Adopt a reflective approach to professional situations, including self-assessment and continuous improvement.

Transversal and Language Skills

• Use standard digital tools and comply with information security rules to acquire, process, produce, and disseminate information, as well as to collaborate internally and externally.
• Identify and select a range of specialised resources to document a subject.
• Analyse and synthesise data for effective use.
• Develop structured arguments with critical thinking.
• Use written and oral English proficiently, both in comprehension and expression.

Bachelor’s degrees in Engineering Sciences (SPI), Electrical Engineering and Automatic Control (EEA), or Computer Science, as well as a first year of a Master’s programme (M1) in the same field (electronics, computer science, and/or signal and image processing).

Doctoral studies (PhD)

• Project Management in Robotics

• Project Management in Industrial Vision

• Data Analysis and Deep Learning

• Engineering Studies and System Design

• Business Development and Applications Engineering

• Automation and Vision Systems Management

• Embedded Systems Development

• Hardware Development Management

• Research and Development in Computer Vision

• Research and Development in Electronics

• Research and Development in Medical Imaging

• Research and Development in Imaging for Agri-food and Agronomy

• Robotics Development

• Academic Teaching and Research

• Technical Sales Engineering in Imaging and Computer Vision