The Embedded Vision Summit is going virtual this year and we’re proud of the program we’ve created! Click on the Schedule at a Glance images to get an overview of the event.
You can now enjoy four main days of learning that are shortened for a more digestible format—we know you may have been getting a lot of screen time lately. Now that the full schedule is here, you can start planning your Summit adventure.
In addition to our usual talks and exhibits, we have some other great opportunities—like Expert Bars, Over the Shoulder Sessions, and Workshops—where you can gain more insights, connect with experts and grow your technical skills.
A VP of the IoT Group and GM of Developer Enabling at Intel leading in the creation of developer tools & solutions that engage developers globally to drive strategic application.
Learn More About Bill Pearson
The Summit prides itself on solely focusing on practical, deployable computer vision and AI. What that means is if your a product developer, engineer or business leader looking for technologies or the most current and future topics in computer vision and AI, we want to give you the tools to hit the ground running once you get back to your office.
We have four robust tracks jam-packed with a wide range of topics:
Past attendees have told us that our session content, demos, exhibits and connections give them the competitive edge they need for developing both their products and professional careers.
Using DevCloud and the Deep Learning Workbench, you will explore the wide range of pre-configured examples available in the Intel DevCloud for the Edge, spanning medical, industrial, retail and education applications. We’ll also introduce tutorials for encrypted models, how to migrate from DevCloud to a local edge device, and DL Streamer Pipeline examples.
Friday, September 18, 9:00 am – 1:30 pm PT
You will use DevCloud to run live demonstrations of benchmarking various trained models executing on specific devices using the Deep Learning Workbench. We will highlight the wide range of retail examples available in the Intel DevCloud for the Edge, including store aisle monitoring, multi-camera store traffic monitoring, and shopper gaze detection. We’ll also introduce tutorials for encrypted models, how to migrate from DevCloud to a local edge device, and DL Streamer Pipeline examples.
Monday, September 21, 9:00 am – 1:30 pm PT
Take a deep dive into the capabilities of Edge Insights for Industrial via a tutorial utilizing a defect detection application example. In this example, printed circuit boards (PCBs) are inspected via video for quality control, including detection of missing components and short circuits.
Wednesday, September 23, 9:00 am – 1:30 pm PT
This Synopsys seminar includes sessions on implementing artificial intelligence, machine learning and computer vision into SoCs, all aimed to help you develop vision chips for edge applications. You’ll deep dive into always-on, low-power applications, implementing gesture recognition, system-level architecture exploration, SLAM implementations, securing sensitive information (from algorithms to biometric data) and much more.
Wednesday, September 16, 9:00 am – 12:00 pm PT
Friday, September 18, 9:00 am – 12:00 pm PT Price: $25
Travel costs you time, energy and money. Now, you can save on all those things and enjoy the Summit from the comfort of your own home!
Depending on your availability, you can experience the online Summit live over several days either or on-demand when you have the time.
This year's move to a virtual event has opened up new and greater opportunities to directly connect with experts throughout the conference.
A very big thanks to @SamsungSDSA for partnering with us at the @EmbVisionSummit and sharing how our Zebra #AI inference accelerator is helping to bring #ML to embedded solutions!
The 2020 Embedded Vision Summit is closing the event today with a bang! Watch this panel discuss a hot topic in edge AI and #ComputerVision. | Sep 24 from 1:30 pm-2:30 pm PT | Reg & info: https://embeddedvisionsummit.com
#EVS20 @aurora_inno @ovt_tech @Applied4Tech @CarnegieMellon