Useful links
We are aiming for an incremental return to campus in accordance with guidelines provided by NSW Health and the Australian Government. Until this time, learning activities and assessments will be planned and scheduled for online delivery where possible, and unit-specific details about face-to-face teaching will be provided on Canvas as the opportunities for face-to-face learning become clear.
We are currently working to resolve an issue where some unit outline links are unavailable. If the link to your unit outline does not appear below, please use the link in your Canvas site. If no link is available on your Canvas site, please contact your unit coordinator.
Unit of study_
COMP5425: Multimedia Retrieval
The explosive growth of multimedia data, including text, audio, images and video has imposed unprecedented challenges for search engines to meet various information needs of users. This unit provides students with the necessary and updated knowledge of this field in the context of big data, from the information retrieval basics of a search engine, to many advanced techniques towards next generation search engines, such as content based image and video retrieval, large scale visual information retrieval, and social media.
| Code | COMP5425 |
|---|---|
| Academic unit | Computer Science |
| Credit points | 6 |
|
Prerequisites:
?
|
None |
|---|---|
|
Corequisites:
?
|
None |
| Prohibitions:
?
|
None |
| Assumed knowledge:
?
|
Experience with programming skills, as learned in COMP9103 OR COMP2123 OR COMP2823 OR INFO1105 OR INFO1905 (or equivalent UoS from different institutions). |
At the completion of this unit, you should be able to:
- LO1. perform functional analysis for specific application domain and specific users
- LO2. conduct literature review in the field related to a given task
- LO3. perform function design of a retrieval system
- LO4. design technical solutions to solve a media retrieval problem with learned knowledge and techniques
- LO5. explain the framework and key components of a general retrieval systems
- LO6. reflect on the state of the art in multimedia retrieval
- LO7. evaluate the advantages and shortcomings of a specific retrieval technique and solution
- LO8. practice popular algorithms related to retrieval techniques, such as feature extraction and similarity measurement.
Unit outlines
Unit outlines will be available 2 weeks before the first day of teaching for 1000-level and 5000-level units, or one week before the first day of teaching for all other units.
There are no unit outlines available online for previous years.
- Key dates
Key dates through the academic year, including teaching periods, census, payment deadlines and exams.
- Student administration
Enrolment, course planning, fees, graduation, support services, student IT
- Expectations of student conduct
Code of Conduct for Students, Conditions of Enrollment, University Privacy Statement, Academic Integrity
- Academic appeals
Academic appeals process, special consideration, rules and guidelines, advice and support
- Learning and teaching policy
Policy register, policy search
- Financial support
Scholarships, interest free loans, bursaries, money management
- Study resources
Learning Centre, faculty and school programs, Library, online resources
- Health and support
Student Centre, counselling & psychological services, University Health Service, general health and wellbeing
