Xilinx & EBV Elektronik Webinar Series: Smart Vision Applications Acceleration for Software Developers

Please select at least one session

Session 1: Smart Vision Market Opportunities, Applications, Challenges
Dec 1. 2020 | 11:00 AM CET
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Session 2: Smart Vision Software Application Development and Acceleration
Dec 2. 2020 | 11:00 AM CET
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Session 3: Smart Vision Live Demo using Vitis and Ultra96 V2
Dec 3. 2020 | 11:00 AM CET
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Accelerating Industrial Vision applications from problem to solution. It does not matter if you are beginner or advanced software developer, working for years with OpenCV or just interested to know-how to translate Convolutional Neural Network into a running application.

Join us and learn how to effectively accelerate and reduce time to market of your high performance vision AI application using the Vitis unified programming paradigm from Xilinx.

Computer Vision and Image Processing are ubiquitous today in a wide range of applications like Robotics, IIoT, Surveillance, Medical Imaging, ADAS, and Video Streaming services and are also a critical part of the end-to-end processing pipeline of AI-powered vision solutions. During this series you will learn how Xilinx can be used to successfully implement and accelerate your application using Vitis Unified Software Platform.From the Neural Network Model to the final inference: AI/ML acceleration within popular software development platforms like Tersor Flow and PyTorch as well as hardware-accelerated open source libraries, Python, C, C++ Support, Apache TVM, pre-trained CNNs – all steps and available tools within Vitis will be explained and presented with real examples.


  • Session 1: Smart Vision Market Opportunities, Applications, Challenges
  • Session 2: Smart Vision Software Application Development and Acceleration
  • Session 3: Smart Vision Live Demo using Vitis and Ultra96V2

Session 1 take-aways:

  • Where the market opportunities are for smart vision applications
  • Key application areas for smart vision
  • How to accelerate your Smart vision Application
  • How to overcome performance obstacles when developing smart vision applications

Session 2 take-aways:

  • How to use standard ML frameworks to implement accelerated smart vision applications
  • Which software components allow you to accelerate smart vision applications more effectively
  • How to translate your Neural Network Model and run it on the real hardware
  • That even without knowing hardware description language, you can use powerful adaptive hardware platform

Session 3 take-aways:

  • How to build your first smart vision application using Xilinx About Tool/IP/Demo/Reference
  • Designs available now for evaluation and development
  • How to step-by-step implement and run the pre-trained Neural Network model
Susan Cheng
Marketing Lead for Industrial Vision



Stan Klinke
Field Application Engineer
EBV Elektronik