How to Get the Best Deep Learning Performance with the OpenVINO Toolkit

Wednesday, May 22, 10:45 AM - 11:15 AM
Summit Track: 
Enabling Technologies
Exhibit Hall ET 2

Tremendous recent progress in deep learning and computer vision algorithms has made it possible to create innovative applications that were not previously feasible. However, moving from academic research to real-world algorithm deployment is still complicated due to the amount of native programming and low-level knowledge that is required to unleash the full performance of processing platforms. This talk will demonstrate how the Intel OpenVINO toolkit makes it easy to move deep learning algorithms from research to deployment. We will walk through the most important toolkit features that allow you to create lightweight applications and reach maximum performance on various processing platforms, including traditional CPUs as well as accelerators such as VPUs, GPUs and FPGAs.


Yury Gorbachev

Principal Engineer, Intel

Yury Gorbachev is a Principal Engineer and Lead Architect for the OpenVINO toolkit at Intel. Yury’s interests are in embedded vision platforms and deep learning. Yury was previously a Principal Engineer at Itseez (acquired by Intel), responsible for embedded platforms and automotive algorithm deployment. Prior to Itseez, Yury was CTO of a Mera Networks business unit focused on embedded solutions and platforms. Yury received a Master of Science degree in math from Nizhny Novgorod State University and has more than 10 years of experience in mobile and embedded systems.

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