US 12,103,530 B2
Vehicle data augmentation
Gautham Sholingar, Sunnyvale, CA (US); and Sowndarya Sundar, Mountain View, CA (US)
Assigned to Ford Global Technologies, LLC, Dearborn, MI (US)
Filed by Ford Global Technologies, LLC, Dearborn, MI (US)
Filed on Apr. 15, 2020, as Appl. No. 16/848,957.
Prior Publication US 2021/0323555 A1, Oct. 21, 2021
Int. Cl. B60W 30/18 (2012.01); B60W 10/10 (2012.01); B60W 10/18 (2012.01); B60W 10/20 (2006.01); G05D 1/00 (2006.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06N 3/08 (2023.01); G06V 10/772 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06V 20/58 (2022.01)
CPC B60W 30/18036 (2013.01) [B60W 10/10 (2013.01); B60W 10/18 (2013.01); B60W 10/20 (2013.01); G05D 1/0212 (2013.01); G05D 1/0231 (2013.01); G06F 18/214 (2023.01); G06F 18/217 (2023.01); G06N 3/08 (2013.01); G06V 10/772 (2022.01); G06V 10/7747 (2022.01); G06V 10/82 (2022.01); G06V 20/56 (2022.01); G06V 20/584 (2022.01); B60W 2420/403 (2013.01); B60W 2555/20 (2020.02)] 20 Claims
OG exemplary drawing
 
1. A system, comprising a management computing device including:
a processor; and
a memory, the memory including instructions executable by the processor to:
receive one or more images from a vehicle, wherein a deep neural network included in a computer in the vehicle has failed to determine an orientation of a first object in the one or more images;
generate a plurality of modified images with a few-shot image translator, wherein the modified images each include a modified object based on the first object, and wherein the few-shot image translator is a generative adversarial network and is trained using a plurality of real-world images and a plurality of synthetic images;
re-train the deep neural network to determine the orientation of the first object based on the plurality of modified images wherein the first object is a vehicle trailer; and
output the re-trained deep neural network.