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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Subject not currently offered - Subject options not available.