Objective
This graduate certificate teaches the skills and techniques required to build Intelligent Sensing Systems that are able to make decisions based on visual and audio sensory signals. The main objectives of this module is to strengthen the participants’ understanding of practical skills and knowledge of application acquired in the courses in respective certificate in a supervised manner. Also, to enable participants to demonstrate their proficiency across all of the skills that they have learned in the course modules and hence be certified as competent at the Certificate level.
Intended Audience
This practice module is targeted at participants who wish to complete the certification process for the Graduate Certificate in “Intelligent Sensing Systems”.
Prerequisites
Participants must have successfully obtained a competent score (or have been exempted from) the three component courses for the Graduate Certificate in Intelligent Sensing Systems as listed in the introduction to the Graduate Certificate page.
Components
- Participants will need to undertake one or more projects to gain practical experience and demonstrate their understanding and mastery of the skills taught in the three component courses. The practice project will require each participant to expend an estimated 10 days of effort. These days are not expected to be contiguous and may stretch over many weeks. These projects may be conducted by individual participants or in teams depending on the nature of the project requirements.
- Each participant is required to sit for an examination on a stipulated date and time.
- The overall grade for the participant will be based on the Practice project and Examination.
- Typical examples of practice module projects in past semesters
Surveillance
- A vision system that recognize, count and correct physical exercises
- Emotion recognition using voice, facial and body posture
- Fall detection using OpenPose
- Person re-identification in crowd surveillance
Healthcare
- Hand washing steps recognition system
- Mouse behavior tracking using 3D deep learning
- Static sign language recognition and translation
Transportation
- Green man estimator: A vision based intelligent pedestrian crossing system
- Image retrieval for location prediction
- Intelligent lane detection and tracking for autonomous vehicle navigation
Manufacture
- Real-time computer interface control with human pose estimation
- Vision-based operator activity recognition for personnel efficiency analysis
