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.
|Date(s):||14 Jan 2019 to 10 May 2019|
|Time:||Refer to Class and Exam Schedules|
|Venue:||NTU Main Campus|
|Closing Date of Registration:||17 Jun 2018|
Full Course Fee :
Singapore Citizen /Singapore PR1 21 to 39 years old :
Singapore Citizen1 40 years or older2 :
Singapore Citizen1 Eligible for WTS3 :
Singapore PRs ≥ 21 years older :
Enhanced Training Support for SMEs4 :
|Method of Payment|
|Withdrawal & Refund Policy|
|Once payment is made, applicant is committed to the completion of course. Course fee refunds will not be considered.|
|Terms and Conditions|
|At PaCE College, participants’ personal information is collected, used and disclosed for the following purposes: