cse5ir image retrieval
IMAGE RETRIEVAL
CSE5IR
2020
Credit points: 15
Subject outline
The explosive growth of digital media data has imposed unprecedented challenges for big multimedia data computing and management. In this subject, you will be introduced to a broad range concepts in image computing and retrieval for multimedia database management. You will learn and apply both the basics of digital image computing. Cutting-edge techniques for multimedia data understanding, content analysis, and image retrieval are practiced, applied, and discussed. With learnt knowledge and techniques, you have the skills to implement an image retrieval model.
SchoolEngineering and Mathematical Sciences
Credit points15
Subject Co-ordinatorLydia Cui
Available to Study Abroad/Exchange StudentsYes
Subject year levelYear Level 5 - Masters
Available as ElectiveNo
Learning ActivitiesN/A
Capstone subjectNo
Subject particulars
Subject rules
PrerequisitesCSE3CI OR CSE5ML OR CSE5CI
Co-requisitesN/A
Incompatible subjectsN/A
Equivalent subjectsN/A
Quota Management StrategyN/A
Quota-conditions or rulesN/A
Special conditionsN/A
Minimum credit point requirementN/A
Assumed knowledgeN/A
Learning resources
Digital Image Processing
Resource TypeBook
Resource RequirementRecommended
AuthorRafael C. Gonzalez, Richard E. Woods
Year2017
Edition/Volume4th edition
PublisherPearson
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Multimedia Information Retrieval and Management Technological Fundamentals and Applications
Resource TypeBook
Resource RequirementRecommended
AuthorD. Feng, W.C.Siu, and H.J.Zhang
Year2003
Edition/Volume2nd ED
PublisherChapman and Hall/ CRC
ISBNN/A
Chapter/article titleN/A
Chapter/issueN/A
URLN/A
Other descriptionN/A
Source locationN/A
Career Ready
Career-focusedNo
Work-based learningNo
Self sourced or Uni sourcedN/A
Entire subject or partial subjectN/A
Total hours/days requiredN/A
Location of WBL activity (region)N/A
WBL addtional requirementsN/A
Graduate capabilities & intended learning outcomes
Graduate Capabilities
Intended Learning Outcomes
Subject options
Select to view your study options…
Melbourne (Bundoora), 2020, Semester 1, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorLydia Cui
Class requirements
Laboratory ClassWeek: 11 - 22
One 2.00 hours laboratory class per week on weekdays during the day from week 11 to week 22 and delivered via face-to-face.
LectureWeek: 10 - 22
One 2.00 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Assessments
Assessment element | Category | Contribution | Hurdle | % | ILO* |
---|---|---|---|---|---|
Assignment 1 - Design and implementation of an image retrieval model (1500 words equivalent) | N/A | N/A | No | 35 | SILO2, SILO3, SILO4 |
Assignment 2 - Presentation of designed image retrieval model (1000 words equivalent) | N/A | N/A | No | 15 | SILO4 |
One 2-hour exam (2000 words equivalent) | N/A | N/A | No | 50 | SILO1, SILO2 |