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ON DEMAND until December 4, 2019
Abstract:
Perhaps one of the largest influencers on the future of machine vision is machine learning, the branch of artificial intelligence that is concentrating and developing the idea that a complex system--like that of machine vision--can learn from the data it collects and analyzes and make decisions with little to no human interaction.
This webinar will explore:
- The trend toward embedded machine learning in machine vision systems, in particular its impact on vision software choices.
- How AI and machine learning could help usher in a new era of cloud-based “inspection as a service” opportunities.
- Hardware and software implications that designers and integrators should consider for vision systems that interact with AI and machine learning.
Register to view the webinar on-demand!
Speaker
 Jonathan Hou Jonathan Hou is Chief Technology Officer at Pleora Technologies, a leading supplier of video interface and capture solutions for the industrial automation, security and defense, and medical imaging markets. In this role, Jonathan oversees Pleora’s research & development efforts and leads the company’s long-term technology vision.
Before joining Pleora, Jonathan was Director of Technology with GlobalVision, where he helped develop new automated quality inspection solutions for print inspection applications. Previously, he held positions in software & engineering management, applications engineering, and software development in the machine vision, video, graphics and networking industries.
He has a Bachelor of Applied Sciences - Computer Engineering from the University of Waterloo in Waterloo, Canada, and a Master of Engineering from McGill University in Montreal, Canada.
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Machine Vision Trends: Embedded Machine Learning
Registration Is Closed
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