Comprehensive course analysis
Who should attend
This is an intermediate course, suitable for professionals interested in vision systems.
- Data scientists who need domain knowledge in vision systems to add more value and insights to their data analytics tasks.
- Engineers who need to design, develop, implement and evaluate software and hardware solutions in various applications of vision systems.
- Project managers who are managing projects and products related with vision systems.
- Working professionals who are seeking to refresh or strengthen existing skills in vision systems.
About the course
This 5-day intensive course will provide participants with the comprehensive knowledge of computer vision methods and technologies, and the practical skills to design and build vision systems to solve real-world problems.
This course will benefit engineers, scientists, and project management professionals who need to design, develop, implement and evaluate software and hardware solutions in various applications of vision systems. Participants will benefit from a careful balance of lectures and practical workshops, and some of the topics covered will include concepts and techniques for vision system, video modelling and representation, video processing and analysis, feature extraction and representation, vision system using machine learning such as detection, recognition, segmentation, design, build and evaluate real-time vision system, etc.
Upon completion of the course, students will be able to:
- Identify the requirements for vision systems in various industrial applications
- Understand the fundamentals of computer vision technology and core vision analytics theories and algorithms
- Design and apply vision analytics algorithms to solve industrial use-case scenarios
- Design and build vision systems in domains such as security surveillance, manufacture, consumer electronic, healthcare, urban solution.
- Assess the performance and usefulness of various vision systems
What Will Be Covered
- Introduction to video analytics and computer vision system
- Foundations of computer vision system: Modelling, processing, feature extraction and representation
- Vision system using machine learning: Detection, recognition, and segmentation
- Design, build and evaluate real-time vision system
- Practical case studies in workshops
Tian Jing currently lectures in the Analytics and Intelligent Systems Practice in the areas of artificial intelligence, data analytics, and machine learning. He received his Ph.D. degree from School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. Prior to j...
Dr Matthew Chua, BEng, CSM, PMP, PhD, is currently a lecturer and principal investigator at the NUS Institute of System Science where he specializes in Medical & Cybernetics Systems. He is overseeing the research programme in Smart Healthcare, Artificial Intelligence and Advanced Robotics. He...
Jen Hong develops algorithms. He specializes in deep learning, image processing and medical image diagnosis. He designs illustrations, web page and posters. He plays piano. He invented a mathematical model to analyze dry eye. He used deep learning to correct medical images. He trained deep learni...
Tzann’s experience spans business and technology strategy, management and operation areas. He currently teaches business, technology and digital product strategy and management, and is the course manager for Digital Product Strategy stackable course. His past advisory engagements included busines...
Wai Kin had spent 6 years as a Senior R&D Engineer specializing in electronic circuit design, development of firmware, PC Sync software and Android application development. He completed his Master of Technology in Software Engineering at the National University of Singapore. He has keen inter...
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