Positionnement dans le cursus
Semestre 5
TC
TC
TC
LV
TC
TC
TC
 
 
P - Intro
Stage
Intersemestre
Semestre 6
TC
TC
TB 1
LV
O 1
 
TC
TC
TB 2
 
O 2
 
P - Citoyen
Semestre 7
M 1
M 1
TB 3
TC
LV
M 1
M 1
TB 3
TC
O 4
O 3
 
P - Tech
Intersemestre
Semestre 9
M 2
M 2
D
LV 2/3
O 6
M 2
M 2
D
 
0 3
 
P - industriel
Intersemestre

Course group - TB3-IPR

TB3 - IMAGE AND PATTERN RECOGNITION

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ECTS credits

5.0

Course Director(s):

  • GAVET Yann

    • General Description:

    Image and Pattern Recognition are mature but exciting and fast developing fields, which underpin developments in cognate fields such as computer vision, image processing, text and document analysis and neural networks. It is closely akin to machine learning, and also finds applications in fast emerging areas such as biometrics, bioinformatics, multimedia data analysis and most recently data science. The objective of this GP is to know the necessary mathematical and computational tools and master the concepts of geometrical characterization of shapes (signals, images, point pattern) to get basic knowledge about machine learning on images for real applications. At the end of this toolbox, the student will be able to manipulate the main aspects of modern geometry, use concepts and results to solve concrete problems, such as the extraction of geometrical, morphometrical and textural information in image analysis as well as the characterization, modeling and simulation of point patterns or spatial object distributions. He will also be able to use some basic machine learning techniques to answer image and pattern recognition applicative problems, such as the automatic detection of cancerous skin lesions in biomedical imaging. Important note: This toolbox will be used

    This GP of 80h consists of three UPs:
    • Mathematical Geometry (33h)
    • Computational Geometry (24h)
    • Applications (23h)

    Links between course units:

    The first UP gives the mathematical tools for the extraction of geometrical, morphometrical and textural information from images. The second UP gives the computational tools to characterize, model and simulate point patterns or spatial objects distributions. The third UP is focused on one or two real applications of image and pattern recognition by using the previous mathematical and computational tools.

    Orientations / Associations with other courses:

    This GP is strongly consistent with the TB « Introduction to Image Processing », as well as with other pedagogic units around the digital sciences: TB High Performance Calculation, MAJ Data Science, TB Fundamentals of EF Calculations, DEFI Big Data...

    Key words: