Yu-Te Cheng

Yu-Te Cheng is a senior deep learning software engineer in the Autonomous Driving group at NVIDIA, where he works on neural architecture search and DNN model training, compression, and deployment for various perception tasks in self-driving fields, including object detection, segmentation, path trajectory generation, and so on. He received his master's degree in robotics from Carnegie Mellon University in 2016.
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Posts by Yu-Te Cheng

Technical Walkthrough 0

Speeding Up Deep Learning Inference Using TensorFlow, ONNX, and NVIDIA TensorRT

This post was updated July 20, 2021 to reflect NVIDIA TensorRT 8.0 updates. In this post, you learn how to deploy TensorFlow trained deep learning models using... 15 MIN READ
Technical Walkthrough 0

Discovering GPU-friendly Deep Neural Networks with Unified Neural Architecture Search

After the first successes of deep learning, designing neural network architectures with desirable performance criteria for a given task (for example, high... 9 MIN READ
Technical Walkthrough 0

Object Detection and Lane Segmentation Using Multiple Accelerators with DRIVE AGX

[caption id="attachment_14898" align="alignright" width="610"] DRIVE AGX is NVIDIA's platform for autonomous driving[/caption] Autonomous vehicles require fast... 17 MIN READ