Study programme 2021-2022Français
Multimedia information retrieval
Programme component of Master's in Computer Science à la Faculty of Science

CodeTypeHead of UE Department’s
contact details
Teacher(s)
US-M1-SCINFO-061-MOptional UEMAHMOUDI SaïdF114 - Informatique, Logiciel et Intelligence artificielle
  • MAHMOUDI Saïd
  • 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

  • Have acquired highly specialised and integrated knowledge and broad skills in the various disciplines of computer science, which come after those within the Bachelor's in computer science.
  • Manage large-scale software development projects.
    • Lead a project by mastering its complexity and taking into account the objectives, allocated resources and constraints that characterise it.
  • Manage research, development and innovation.
    • Understand unprecedented problems in computer science and its applications.
    • Methodically research valid scientific information, lead a critical analysis, propose and argue potentially innovative solutions to targeted problems.
  • 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.
    • Pursue further training and develop new skills independently.
  • Apply scientific methodology.
    • Critically reflect on the impact of IT in general, and on the contribution to projects.

Learning Outcomes of UE

Be able to propose and implement multimedia retrieval methods  Search engines optimization techniques

Content of UE

Content based images retrieval approaches applied to multimedia searches engines 
Large multimedia databases management annotation

Prior Experience

Not applicable

Type of Assessment for UE in Q1

  • Presentation and/or works
  • Oral examination
  • Written examination
  • Practical test

Q1 UE Assessment Comments

Not applicable

Type of Assessment for UE in Q3

  • Presentation and/or works
  • Oral examination
  • Written examination

Q3 UE Assessment Comments

Not applicable

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 : 17/09/2021
20, place du Parc, B7000 Mons - Belgique
Tél: +32 (0)65 373111
Courriel: info.mons@umons.ac.be