Objectives of Programme's Learning Outcomes

• Imagine, implement and operate systems/solutions/software to address a complex problem in the field of electrical engineering as a source of information by integrating needs, contexts and issues (technical, economic, societal, ethical and environmental).
• Identify complex problems to be solved and develop the specifications with the client by integrating needs, contexts and issues (technical, economic, societal, ethical and environmental).
• Based on modelling and experimentation, design one or more systems, solutions or hardware and/or software implementations, addressing the problem raised; evaluate them in light of various parameters of the specifications.
• Implement a chosen system/solution/software/circuit in the form of a schema, a flowchart, an algorithm, a prototype, a programme and/or digital model.
• Evaluate the approach and results for their adaptation (tests, measurements, optimisation and quality).
• Mobilise a structured set of scientific knowledge and skills and specialised techniques in order to carry out electrical engineering missions, with a focus on Multimedia and Telecommunications, using their expertise and adaptability.
• Master and appropriately mobilise knowledge, models, methods and techniques related to the basics of electricity, electronics, automatic control, signal processing and analysis, telecommunications, advanced electronics and advanced microelectronics, computer science, wired and wireless telecommunications, signal processing, and human-machine interfaces.
• Analyse and model a problem by critically selecting theories and methodological approaches (modelling, calculations), and taking into account multidisciplinary aspects.
• Identify and discuss possible applications of new and emerging technologies in the field of electrical engineering.
• Assess the validity of models and results in view of the state of science and characteristics of the problem.

Learning Outcomes of UE

develop an applied image and/or video processing system, together with a critical analysis of the problem;
understand image coding techniques (entropy coding, predictive, transform i.e. DCT, DWT), applied digital image analysis (low-level and high-level methods for denoising, segmentation,...) and video analysis and processing methods.

Content of UE

low-level image processing (erosion, dilatation, …); image understanding (analysis, denoising, segmentation, watershed, active contours); video processing; image coding (entropy coding, lossless coding, predictive coding, transform coding, motion prediction); compression standards (JPEG, MPEG 1, 2, 4, 7). Smart Spaces: Attention Analysis, Motion Capture, Interractions

Prior Experience

fundamentals of signal processing (sampling and quantization).

Type of Assessment for UE in Q1

• Oral examination

Q1 UE Assessment Comments

Not applicable

Type of Assessment for UE in Q3

• Oral examination

Q3 UE Assessment Comments

Not applicable

Type of Resit Assessment for UE in Q1 (BAB1)

• N/A

Q1 UE Resit Assessment Comments (BAB1)

Not applicable