Pedestrian Detection on a NVIDIA GPU with TensorRT
3,150 views · Published 3 May 2018 · 1:35 · Indexed 14 November 2026
Channel: MATLAB · 2018 · Science & Technology
Learn how you can generate CUDA® code from a trained deep neural network in MATLAB® and leverage the NVIDIA® TensorRT™ library for inference on NVIDIA GPUs. The video demonstrates this by using a pedestrian detection application as an example. NVIDIA GPU Support from GPU Coder: http://bit.ly/2qEZYSt The NVIDIA TensorRT library is a high-performance deep learning inference optimizer and runtime library. The generated code leverages the network-level and layer-level TensorRT APIs to get the best performance, and you see the neural network for pedestrian detection running on a NVIDIA Titan XP around 700 fps. You can export the generated code along with the rest of the application and deploy the algorithm on embedded GPU targets such as Jetson Tegra® or Drive™ PX platforms. Get a free product Trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See What's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2018 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names maybe trademarks or registered trademarks of their respective holders.
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