Machine Learning and Vision Systems

Course aim

To develop analytic knowledge and skills of machine learning and vision systems and digital image processing for use in mechatronic systems especially in manufacturing applications

Course content

Components of machine vision systems, image acquisition, point and neighbourhood image enhancement, edge based and region based image segmentation, colour image processing, morphological image processing, image description and representation, machine learning fundamentals, Fuzzy logic, Neural networks, basic deep learning.

Textbook(s)

Chris Solomon and Toby Breckon 2011, Fundamentals of Digital Image Processing (A practical approach with Examples in Matlab), - , Wiley - Blackwell

Prerequisite(s)

Nil

Corequisite(s)

Nil

Teaching method

Component	Duration
INTERNAL, MAWSON LAKES
Lecture	2 hours x 13 weeks
Computer Practical	2 hours x 13 weeks

Note: These components may or may not be scheduled in every study period. Please refer to the timetable for further details.

Assessment

Case study, Skills demonstration, Test/Quiz, Viva Voce

Fees

EFTSL*: 0.125
Commonwealth Supported program (Band 2)
To determine the fee for this course as part of a Commonwealth Supported program, go to:
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Fee-paying program for domestic and international students
International students and students undertaking this course as part of a postgraduate fee paying program must refer to the relevant program home page to determine the cost for undertaking this course.

Non-award enrolment
Non-award tuition fees are set by the university. To determine the cost of this course, go to:
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Not all courses are available on all of the above bases, and students must check to ensure that they are permitted to enrol in a particular course.

* Equivalent Full Time Study Load. Please note: all EFTSL values are published and calculated at ten decimal places. Values are displayed to three decimal places for ease of interpretation.