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Who should attend
This is an intermediate course and is applicable for professionals engaged in the following areas:
- Data Scientist, Software Engineer, System Architecture, who need sensor signal processing skills to design and build systems that make decisions by recognizing complex patterns in data.
- IT professionals, who are managing projects and products related with intelligent sensing systems.
About the course
Sensor and sensing technology has emerged as the primary enabling technology for a wide range of applications over the past decades, and will continue to contribute to be the core component of future technologies, such as multimedia systems, Internet of Things, control system, as well as cross-disciplinary applications with pattern recognition and artificial intelligence. This intelligent sensing and sense making course presents the core theory and algorithms of signal processing fundamentals, and practical signal processing skills and strategies for real-world industrial implementations through workshop sessions.
In this 4-day course, participants will learn two key skills: (i) Performing analysis of sensor data using spatial filtering and frequency and statistical analysis; (ii) Building Intelligent systems that utilise advanced signal and sensor data processing. At the end of this course, students will be able to build intelligent systems such as smart machine diagnostic systems, smart healthcare monitoring systems, etc.
This course is part of the Artificial Intelligence and Graduate Certificate in Pattern Recognition Systems Series offered by NUS-ISS.
At the end of the course, the participants will be able to:
- Identify needs of intelligent sensing technology in various industrial applications;
- Acquire knowledge of core intelligent sensing theories, analyze various signal processing models and algorithms;
- Design, apply and evaluate the performance of various intelligent sensing and sense making techniques.
What Will Be Covered
This course will cover:
- Introduction to intelligent sensing systems;
- Foundations of sensor signal processing in spatial and frequency domain;
- Statistical sensor signal analysis;
- Sensor signal processing using machine learning technique;
- Design and build sensor signal processing system to make sense of sensor data.
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...
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...
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