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Tuesday, June 14, 2022 | 9:00am - 10:00am PT

This webinar presents interoperatibilty between VPI and PyTorch and showcases how easy it is to use VPI algorithms in PyTorch applications. We take as an example a Python-based application which captures an input video and uses VPI to reduce noise, improving object detection done by PyTorch. The input video frames are shared from VPI to PyTorch and back without copying data.

In this webinar you will learn:
  • How to program VPI with Python
  • How to use the Temporal Noise Reduction computer vision algorithm in VPI
  • How to share data between VPI and PyTorch avoiding copies
In this webinar you will learn:
  • New Jetson features like the Python GPIO library
  • The anatomy of a typical AI project using Jetson Nano
  • How to train a neural network for a custom task, like avoiding collisions with JetBot 
  • How to easily perform real-time object detection with Jetson Nano
  • How to move beyond JetBot and create your own project

Join us after the presentation for a live Q&A session.

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DGX Station Datasheet

Get a quick low-down and technical specs for the DGX Station.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.

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André de Almeida Maximo

Sr. System Software Engineer, Computer Vision

Andre Maximo is a system engineer at NVIDIA focused on software for embedded platforms. He previously worked for research centers at multiple industrial companies helping shape artificial intelligence across different industries. In his free time, Andre likes to run and read fictional books.

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Webinar: Description here

Date & Time: Wednesday, April 22, 2018