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15:01 Video length is 15:01.
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Deep Learning with MATLAB, NVIDIA Jetson, and ROS

From the series: Implementation

Jon Zeosky and Sebastian Castro discuss how algorithms designed in MATLAB® can be deployed as standalone CUDA® code to target NVIDIA® GPUs, and how this standalone code can be used in a development process involving Robot Operating System (ROS).

In the software demonstration, Jon and Sebastian first use a pretrained neural network in MATLAB to create a deep learning classification algorithm. Then, they use GPU Coder™ to generate a standalone library from this algorithm and deploy it to an NVIDIA Jetson™ platform. Finally, they integrate the generated library into a ROS node developed in C++ to connect with other software nodes running on the network.

Download the example files used in this video from MATLAB Central File Exchange.

Learn more with the following resources:

  • NVIDIA GPU Support from GPU Coder
  • Deep Learning Support from GPU Coder
  • Getting started with MATLAB, Simulink, and ROS

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  • GPU Coder
  • Deep Learning Toolbox
  • ROS Toolbox

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