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Abstract:
This session will discuss the process of training deep neural networks using NVIDIA DGX servers at BMW Group. We will describe our research work in four application areas: fine-grained vehicle representations for autonomous driving, panoptic segmentation, self-supervised learning of the drivable area for autonomous vehicles and neural network optimization. All of these projects require high-performance compute and demand a scalable, agile and adaptive learning infrastructure, leveraging Kubernetes on NVIDIA DGX servers.
This session will discuss the process of training deep neural networks using NVIDIA DGX servers at BMW Group. We will describe our research work in four application areas: fine-grained vehicle representations for autonomous driving, panoptic segmentation, self-supervised learning of the drivable area for autonomous vehicles and neural network optimization. All of these projects require high-performance compute and demand a scalable, agile and adaptive learning infrastructure, leveraging Kubernetes on NVIDIA DGX servers.  Back
 
Topics:
Autonomous Vehicles, AI & Deep Learning Research
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9892
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