In Industry 4.0, digital technologies make manufacturing more agile, flexible and responsive to the customers. Nowadays, it is able to have a smart and digital factory where advanced technologies (IoT, 5G, Machine Learning, Deep Learning, etc.) work together to optimize the manufacturing process and improve customer satisfaction.
Machine vision systems together with automated image-based analysis offer manufacturers a certain level of assurance in product quality inspection. For inspection in quality assurance process, deep learning turn out to be a game changer as it is powerful in the way of mimicking human intelligence to distinguish anomalies in complex patterns.
The attendees will become familiar with the principles of deep learning technologies. The process to develop a deep learning model which work as expected will be described in the course. Typical applications using deep learning technologies and deep learning research directions will be discussed and explained.
This course consists of 3 full-day sessions covering hands-on session using both commercial software and open source networks for developing deep learning models. This would enhance the understanding of deep learning principles. At the end of the course, the attendees will be able to develop deep learning models for their potential inspection applications.
Who Should Attend
This course is relevant for business owners and management with intention to have a first understanding of or to develop capability of deep learning for industry intelligent inspection applications.
Moreover, it is applicable to Individuals and staff who are currently employed or wish to be employed in visual inspection/image processing related fields, seeking to have a first understanding of the deep learning technologies. A typical candidate profile could be:
- Quality Control Manager/Engineer
- Machine Learning Engineer
- Production Supervisor/Manager