Study programme 2020-2021Français
Multimedia information retrieval
Programme component of Master's in Computer Science à la Faculty of Science

Students are asked to consult the ECTS course descriptions for each learning activity (AA) to know what special Covid-19 assessment methods are possibly planned for the end of Q3

CodeTypeHead of UE Department’s
contact details
Teacher(s)
US-M1-INFO60-038-MCompulsory UEMAHMOUDI SidiF114 - Informatique, Logiciel et Intelligence artificielle
  • MAHMOUDI Sidi

Language
of instruction
Language
of assessment
HT(*) HTPE(*) HTPS(*) HR(*) HD(*) CreditsWeighting Term
  • Anglais
Anglais181800033.001st term

AA CodeTeaching Activity (AA) HT(*) HTPE(*) HTPS(*) HR(*) HD(*) Term Weighting
I-ILIA-014Machine & Deep Learning for Multimedia Retrieval1818000Q1100.00%
Programme component

Objectives of Programme's Learning Outcomes

  • Carry out development or innovation projects in IT.
    • Master the complexity of such work and take into account the objectives and constraints which characterise it.
  • Master communication techniques.
    • Communicate, both orally and in writing, their findings, original proposals, knowledge and underlying principles, in a clear, structured and justified manner.
  • Develop and integrate a high degree of autonomy.
    • Aquire new knowledge independently.
  • Apply scientific methodology.
    • Critically reflect on the impact of IT in general, and on the contribution to projects.
    • Demonstrate thoroughness, independence, creativity, intellectual honesty, and ethical values.

Learning Outcomes of UE

At the end of this teaching unit, the student would be able to:
- develop methods for searching, navigation and indexing multimedia databases;
- exploit deep learning techniques for searching and indexing multimedia databases.

Content of UE

- 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).
 

Prior Experience

Not applicable

Type of Assessment for UE in Q1

  • Presentation and/or works
  • Oral examination
  • Graded tests

Q1 UE Assessment Comments

Project evaluated within report and presentation
Practical test evaluated within program quality and performance

Type of Assessment for UE in Q3

  • Presentation and/or works
  • Oral examination
  • Graded tests

Q3 UE Assessment Comments

Idem Q1

Type of Resit Assessment for UE in Q1 (BAB1)

  • N/A

Q1 UE Resit Assessment Comments (BAB1)

Not applicable

Type of Teaching Activity/Activities

AAType of Teaching Activity/Activities
I-ILIA-014
  • Cours magistraux
  • Conférences
  • Travaux pratiques
  • Travaux de laboratoire
  • Projet sur ordinateur

Mode of delivery

AAMode of delivery
I-ILIA-014
  • Mixed

Required Reading

AA
I-ILIA-014

Required Learning Resources/Tools

AARequired Learning Resources/Tools
I-ILIA-014Not applicable

Recommended Reading

AA
I-ILIA-014

Recommended Learning Resources/Tools

AARecommended Learning Resources/Tools
I-ILIA-014Not applicable

Other Recommended Reading

AAOther Recommended Reading
I-ILIA-014Not applicable

Grade Deferrals of AAs from one year to the next

AAGrade Deferrals of AAs from one year to the next
I-ILIA-014Unauthorized
(*) 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
Date de génération : 09/07/2021
20, place du Parc, B7000 Mons - Belgique
Tél: +32 (0)65 373111
Courriel: info.mons@umons.ac.be