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Deep Learning for Autonomous Vehicles Perception

This workshop teaches you to apply deep learning techniques to design, train, and deploy deep neural networks for autonomous vehicles using the NVIDIA DRIVE development platform through a series of hands-on exercises. You will work with widely-used deep learning tools, frameworks, and workflows by performing neural network training on a fully-configured GPU accelerated workstation in the cloud. The workshop starts with an introduction of Sensor Abstraction Layer (SAL) which is required for software to interface with the hardware sensors. After covering SAL and concepts on DRIVE PX, we teach you the steps required to do semantic segmentation on DRIVE PX and conclude by teaching techniques to leverage TensorRT, a high-performance neural network inference engine for production deployment of deep learning applications, to optimize, validate, and deploy trained neural network for inference in a self-driving car application.

Course Prerequisites

  • Experience with CNNs

Deep Learning for Autonomous Vehicles Perception Key Facts
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