 | Study programme 2022-2023 | Français | |
| Computer Vision & Machine Intelligence | |||
Learning Activity |
| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) | Establishment |
|---|---|---|---|---|
| I-ISIA-005 |
|
|
|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Anglais | Anglais, Français | 24 | 24 | 0 | 0 | 0 | Q1 |
Content of Learning Activity
Image Processing, Image acquisition; lowlevel processing, filtering, transforms; image segmentation and registration;
Image Coding, Deep Learning
Teaching modalities may be adjusted according to the teaching context imposed by health measures.
Required Learning Resources/Tools
Not applicable
Recommended Learning Resources/Tools
Not applicable
Other Recommended Reading
Not applicable
Mode of delivery
- Hybrid
Type of Teaching Activity/Activities
- Cours magistraux
- Travaux pratiques
- Projet sur ordinateur
- Etudes de cas
Evaluations
The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)
(*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term