Democratizing Machine Vision with Embedded AI

File:Sick-Logo-Claim 4c.png - Wikimedia Commons

in Linköping make smart cameras that let non-experts solve industrial machine vision applications with ease.

In this presentation we will give an insight into the world of industrial machine vision. We will do a live demo of our products, and discuss interesting challenges involved in making an easy-to-use solution, enabled by machine learning running directly on the embedded device.

SICK IVP in Linköping has a long history of machine vision, combining deep technical expertise with a strong focus on usability and customer value.

Do you have questions?
Feel free to contact me
christoffer.kamronn@linkopingsciencepark.se

Program

12:00-12:10 Check-in & Lunch
12:10-12:45 Presentation & Lunch
12:45-12:55 Q&A

Speakers

Viktor Smedby is Strategic Product Manager for Machine Vision at SICK. With over a decade of experience in machine vision and computer vision, Viktor oversees the development and lifecycle of a range of 2D integrated vision devices, Edge Learning / AI, and vision software. Prior to joining product management Viktor worked extensively with engineering and development of vision applications, spanning topics such as robot guidance, quality control, and high-performance 3D imaging.

Erik Hedberg is one of the key developers in the team behind SICK’s AI edge learning algorithms, with a keen interest in balancing usability and performance. Erik has an academic background in control and estimation, with a licenciate degree in Automatic Control from Linköping University, and coordinates SICK’s educational collaboration with the university.

Tid

12:00–13:00

Plats

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