English versionStudyGRADUATEEngineering Programme "diplôme d'ingénieur"> Course specialisations YRS 2&3
Data analysis and applications in signal and image processing
Objectives
- Overview
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The objective of this specialisation is to train multidisciplinary engineers to design and implement methodological and algorithmic solutions to data processing problems in various industrial application fields.
Courses are based on the theory and the practice of methods from computational statistics, applied mathematics, signal and image processing, as well as applied computer science and scientific computing. These courses also offer application-oriented content from healthcare, research and development, imaging science, information and communication technology.
This specialisation confers Centrale engineers the skills needed for a professional orientation to research and innovation in industrial and academic fields related to data sciences, audio engineering, industrial imaging, computer-aided decision and biomedical engineering.Contribution to sustainable development goals
- Admission
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International students can follow this specialisation, taught in French, via:
- A double degree programme - Open to international students selected by our partner institutions. Selected students spend two years studying courses from the engineering programme at Centrale Nantes. This usually includes one year of the common-core engineering curriculum followed by one year of specialisation. Double degree students are typically accepted after successfully completing two or three years of higher education in their home institution.
- The fast-track engineering programme: Open to students with a Bachelor's or equivalent degree in science. Our fast-track programme gives international students who are qualified to bachelor level the opportunity to gain the 'diplôme d'ingénieur' in just two years.
- Course Content
- 2023/24 Academic Year
Autumn Semester Spring Semester Signal representation and analysis R&D applications Image processing and analysis Audio content analysis and information retrieval Scientific computing and numerical optimization Advanced machine learning and medical imaging Statistical data modelling and analysis Multi-sensor data analysis Graph theory and time series analysis Project in signal and image processing Machine learning theory and practice Internship Imaging and inverse methods Filtering and biomedical signal processing Project in signal and image processing - Examples of projects and internships
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Examples of past projects
- Joint detection-estimation of hymodynamic responses from functional MRI data
- Ultrasound data analysis for depth estimation in non-destructive testing
- Convex k-means clustering from approximate pairwise comparisons
- Unsupervised data clustering for acoustic quality assessment in urban areas
- Implementation of deep learning algorithms for CT scan image segmentation
- Optimization of a Brain-Computer Interface including a Virtual Reality feedback
- Online acquisition and unmixing of hyperspectral images
Examples of past internships
- Short-term audio source separation filter estimation from recurrent convolutional networks (Orange, Rennes)
- Automatic detection of vine rows on aerial images (Avion Jaune, Paris)
- Predicting the risk of delays for the operation of major train stations (SNCF, Paris)
- Correlation between foot and hand movement in pedestrian navigation (IFSTTAR, Nantes)
- Machine learning on biomedical images (CHU Nantes)
- Evaluation of the mental load induced by a brain-computer interface system coupled with virtual reality (OnePoint and CHU Nantes)
- Development of an image processing algorithm for the correction of artifacts in 2D and 3D mammography acquisitions (GE Healthcare, The Netherlands)
- After the specialisation
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Industry Sectors
- Data sciences
- Biomedical engineering
- Digital, sound and multimedia
- Industrial R&D (troubleshooting, decision support)
- ICT
Career Prospects
- R&D engineer
- Data scientist
- Digital applications design
- Data acquisition and processing project manager