cse4prn pattern recognition
PATTERN RECOGNITION
CSE4PRN
Not currently offered
Credit points: 15
Subject outline
This subject provides students with advanced knowledge in neural networks and related pattern recognition techniques. Main topics include: introduction to pattern recognition; discriminative versus generative approaches; multilayer perceptrons; radial basis function networks; support vector machines; mixture models and the Expectation-Maximization algorithm; Bayesian methods; support vector machines, and Kohonen Networks. Case studies in bioinformatics and document categorization are included. Assignments offer students a sufficiently large space to explore neural networks and related pattern recognition techniques in terms of both theoretical issues and applications in the real world.
SchoolEngineering and Mathematical Sciences
Credit points15
Subject Co-ordinatorAndrew Skabar
Available to Study Abroad/Exchange StudentsYes
Subject year levelYear Level 4 - UG/Hons/1st Yr PG
Available as ElectiveNo
Learning ActivitiesN/A
Capstone subjectNo
Subject particulars
Subject rules
Prerequisites CSE3ISE (from 2009 CSE3CI)
Co-requisitesN/A
Incompatible subjectsCSE4NN
Equivalent subjectsN/A
Quota Management StrategyN/A
Quota-conditions or rulesN/A
Special conditionsN/A
Minimum credit point requirementN/A
Assumed knowledgeN/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
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