Signal and Image Processing (CORO SIP)
Master
In Nantes (France)
Establish a relevant statistical model for data representation and analysis
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Type
Master
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Location
Nantes (France)
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Duration
2 Years
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Start date
September
The Signal and Image Processing (SIP) programme provides the necessary skills in signal modelling, image processing and machine learning, relevant to the theory and the practice of data analysis and information retrieval, for the development of modern numerical methods.
The courses of SIP programme address the theory and the practice of advanced data analysis techniques, from computational statistics, applied mathematics, scientific computing and numerical imaging, to their practical implementation in several fields such as biomedical engineering, imaging science, audio processing and information technology.
The key feature of the programme is the design of mathematical solutions, for signal and image processing problems, accounting for the physical specificities of this data and adapting the numerical implementation of these solutions to the application context, the data amount and the available computational resources.
The programme of study lasts two academic years - denoted by M1 and M2. Signal and Image Processing is one of four specialisms available within the Control and Robotics stream. Some of the M1 courses are the taught across the four specialisms whereas the M2 courses are specialism-specific. See course content for more details. The language of instruction is English across the two years.
Important information
Documents
- MASTER CORO-SIP_web2019.pdf
Facilities
Location
Start date
Start date
About this course
The main objectives are: to establish a relevant statistical model for data representation and analysis, to propose a methodological solution and its numerical implementation suited to the application context and to acquire a solid background on real-life applications of signal and image processing in research and innovation
Students must have: a bachelor's degree in Engineering, Science or Technology, or a 'license' qualification or equivalent. Applicants must have a good level in Mathematics and be fluent in English - written and spoken. An applicant whose native language is not English is required to pass a recognised international test of English (TEOFL, IELTS, TOEIC or Cambridge Advanced English Test). Applicants who carried out their studies in English may provide an official letter from their university stating that the language of instruction was English in place of one of the approved English tests.
This program provides good prospects for employment or further study. Former students have worked in the following feilds and sectors: biomedical engineering, industrial imaging, audio engineering, computer science, Applied mathematics, research and innovation, health, communication, technology, transportation. Some positions that alumni have held: data analyst, research scientist, process engineer, design engineer, research and innovation engineer (post PhD)
Reviews
Subjects
- Computational
- Biomedical
- Imaging
- English
- Data analysis
- Computing
- Image
- Project
- Systems
- Machine Learning
- Information
- Computation
- Signal filter
- Embedded computing
- Digital signal
Teachers and trainers (1)
Teacher´s Team
Teacher
Course programme
30 ECTS Credits per semester.
Autumn Semester Courses
- Signal Processing
- Classical Linear Control
- Artificial Intelligence
- Embedded Electronics
- Systems Identification and Signal Filtering
- Embedded Computing
- Modern Languages *
- Group Project
- Optimization Techniques
- Mobile Robots
- Programming Real Time Systems
- Computer Vision
- Spectral and Time Frequency Analysis
- Modern Languages *
* 'French as Foreign Language' except for French native speakers who will study 'Cultural and Communicational English'
NB Course content may be subject to minor changes
Course Content - M2
30 ECTS Credits per semester
Autumn Semester Courses
- Statistical signal processing and estimation theory
- Digital signal and image representations
- Machine learning, data analysis and information retrieval
- Signal and image restoration, inversion methods
- Mathematical tools for signal and image processing
- Biomedical signals, images and methods
- Modern Languages *
- Project
- Conferences
* 'French as Foreign Language' except for French native speakers who will study 'Cultural and Communicational English'
Spring Semester
Master Thesis/Internship
Examples of previous internships in Medicine:
- Analysis of Electromyographic signals for neuromuscular disease characterization
- Reconstruction of Positron Emission Tomography images in the context of low statistics
- Resolution enhancement in Magnetic Resonance Imaging for cardiovascular diagnosis
Examples of previous internships in industry:
- Optimization of a tyre pressure monitoring system in an automotive vehicle
- Fast imaging algorithm for structured illumination microscopy
Examples of previous internships in research labs:
- Numerical optimization for sparse ultrasound signal recovery
- Analysis and classification of environmental sounds using deep learning methods
NB Course content may be subject to minor changes
Signal and Image Processing (CORO SIP)