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.

Posts by Yu-Te Cheng

AI / Deep Learning

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… 9 MIN READ
AI / Deep Learning

Speeding up Deep Learning Inference Using TensorFlow, ONNX, and TensorRT

Starting with TensorRT 7.0, the Universal Framework Format (UFF) is being deprecated. In this post, you learn how to deploy TensorFlow trained deep learning… 15 MIN READ
Autonomous Vehicles

Object Detection and Lane Segmentation Using Multiple Accelerators with DRIVE AGX

Autonomous vehicles require fast and accurate perception of the surrounding environment in order to accomplish a wide set of tasks concurrently in real time. 17 MIN READ