 | Study programme 2021-2022 | Français | |
| Machine & Deep Learning for Multimedia Retrieval | |||
Learning Activity |
| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) | Establishment |
|---|---|---|---|---|
| I-ILIA-014 |
|
|
|
| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Anglais | Anglais | 18 | 18 | 0 | 0 | 0 | Q1 |
Content of Learning Activity
- Content based images retrieval approaches applied to multimedia searches engines
- Large multimedia databases management annotation
- Features extraction using classic methods and convolutional neural networks (CNN).
Required Learning Resources/Tools
Not applicable
Recommended Learning Resources/Tools
Not applicable
Other Recommended Reading
Not applicable
Mode of delivery
- Mixed
Type of Teaching Activity/Activities
- Cours magistraux
- Conférences
- Travaux pratiques
- Travaux de laboratoire
- Projet sur ordinateur
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