Search
Menu
Rocky Mountain Instruments - Custom Assemblies LB

Hybrid AI Reduces Inspection Errors, Costs, and Risk

Jul 20, 2021
Facebook X LinkedIn Email
TO VIEW THIS WEBINAR:
Login  Register
Sponsored by
Pleora Technologies Inc.
About This Webinar
Manufacturers and brand owners navigating through the complexities of AI are left with a few key questions: How can AI reduce errors and automate manual tasks? Is algorithm training expensive or complicated? Can I keep existing infrastructure and processes?

Jonathan Hou discusses hybrid AI, a unique approach that merges the best of computer vision and machine learning to address these key concerns and allow manufacturers to deploy advanced end-to-end quality inspection.

He examines how AI addresses critical quality challenges in the consumer goods, print and packaging, and parts manufacturing markets to increase profitability and reduce risk. Hou outlines hybrid AI training and deployment strategies for established automated inspection systems, as well as opportunities for adding decision support to manual tasks. To close the session, he presents a case study on how a consumer brand is deploying hybrid AI today while also preparing for more advanced Industry 4.0 and IIoT automation.

***This presentation premiered during the 2021 Vision Spectra Conference. For more information on Photonics Media conferences, visit events.photonics.com.

About the presenter:
Jonathan HouJonathan Hou is president of Pleora Technologies, a leading supplier of AI, embedded, and sensor networking solutions for the industrial automation, security and defense, and medical imaging markets. He oversees Pleora's research and development efforts and leads the company's long-term technology vision.

Hou joined Pleora as CTO in 2018. Previously he was director of technology with GlobalVision, where he helped develop new automated quality inspection solutions for print inspection applications. He has held positions in software and engineering management, applications engineering, and software development in the machine vision, video, graphics, and networking industries. He has a Bachelor of Applied Science in Computer Engineering from the University of Waterloo in Waterloo, Canada, and a Master of Engineering from McGill University in Montreal.
artificial intelligenceautomationmachine visionVision Spectrahybrid AImachine learning
We use cookies to improve user experience and analyze our website traffic as stated in our Privacy Policy. By using this website, you agree to the use of cookies unless you have disabled them.