In recent years, computational intelligence methods like artificial neural networks, fuzzy systems, genetic algorithms and computer vision are applied extensively in the design of intelligent control and automation systems, e.g. autonomous vehicles, visual inspection of industrial products, automated analysis and screening of volumes of medical images.
The objective of this design module is to provide participants an opportunity to study some selected aspects of computational intelligence methods in-depth and to develop and test an intelligent automation systems.
The module will focus on Feature Extraction and Object Recognition using computer vision as part of an intelligent system design. It comprises 13 hours of lectures and 26 hours of hands on sessions.
a) Appreciate the applications of computer vision in intelligent systems design.
b) Acquire an in-depth knowledge in structural object recognition by relational graph matching and feature extraction.
c) Able to choose suitable attributes to represent the objects, design appropriate pre- processing algorithms and feature extraction algorithms in order to perform the recognition by relational graph matching for a given structural object recognition problem.
d) Acquire substantial hands-on-experience in the relevant aspects of computer vision.
Eligibility Criteria
At least 21 years of age
Have 2 years of full-time work experience, or have fully discharged full-time NS liability, or are currently employed on a full-time basis.
Degree in Engineering/Science or
Polytechnic Diploma with relevant working experience
Programme Duration
Date(s): 12 Aug 2019 to 6 Dec 2019
Time: Refer to Class and Exam Schedules
Venue: TR103
Closing Date of Registration: 16 June 2019
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