Create customized stereovision solutions with Onsemi IAS global shutter camera modules, Zynq UltraScale+ on the Ultra96 platform, and Xilinx Vivado HLS.


Vision is a foundational sensing technology in a growing number of fields. In this webinar, presenters will discuss considerations of such imaging solutions and expand on the advantages and techniques of implementing such solutions with Xilinx’s Zynq UltraScale+ on Avnet’s Ultra96 platform. There will be a thorough overview of how Xilinx Vivado HLS gives way to scalable image processing.


What You Will Learn In This Webinar:


  • Considerations to take when designing an imaging solution
  • Show how to use High Level Synthesis (HLS) to configure the field programmable gate array (FPGA)
  • Explain how to build the real-time video processing pipelines in Xilinx Vivado HLS
  • Review the advantages of using FPGA’s in vision systems






Buy KitBuy Kit


The Presenters:


image image
Griffin Peterson, Image Sensor Specialist at Avnet Chris Ammann, Global Technical Marketing Engineer at Avnet
Griffin Peterson (BSE Electrical Engineering, University of Michigan) is a vision solutions expert. He is an entrenched resource in image sensing technologies, camera module design and supply chains, and image processing pipelines. He previously worked in Onsemi’s image sensing group and has been an Image Sensor Specialist at Avnet since 2018.

Started my career designing equipment for telecom with a focus on power and harsh environments. Joined Avnet as a power specialist FAE, eventually moving on to a role with the Global team focused on power. I now support power and thermal design around all the Avnet designed products as well as work with manufacturers to create material that helps customers tailor power solutions to their end products.


Kevin Keryk, Marketing Manager at Avnet
Kevin Keryk is a computer engineer by degree, a technical marketing manager by day, and embedded software programming addict from an impressionable age which has turned into a mostly healthy fascination with FPGAs, Programmable Logic, and other hardware craft over the past 10 years at Avnet. He now leads a small but agile group of Machine Learning Engineers who specialize in AI at the Edge applications across a wide range of advanced devices