US 11,688,181 B2
Sensor fusion for autonomous machine applications using machine learning
Minwoo Park, Saratoga, CA (US); Junghyun Kwon, Santa Clara, CA (US); Mehmet K. Kocamaz, San Jose, CA (US); Hae-Jong Seo, Campbell, CA (US); Berta Rodriguez Hervas, San Francisco, CA (US); and Tae Eun Choe, Belmont, CA (US)
Assigned to NVIDIA Corporation, Santa Clara, CA (US)
Filed by NVIDIA Corporation, Santa Clara, CA (US)
Filed on Jun. 21, 2021, as Appl. No. 17/353,231.
Claims priority of provisional application 63/043,794, filed on Jun. 25, 2020.
Claims priority of provisional application 63/047,205, filed on Jul. 1, 2020.
Prior Publication US 2021/0406560 A1, Dec. 30, 2021
Int. Cl. G06V 20/58 (2022.01); G06V 20/56 (2022.01); B60W 60/00 (2020.01); G06T 7/292 (2017.01)
CPC G06V 20/588 (2022.01) [B60W 60/00272 (2020.02); G06T 7/292 (2017.01); G06V 20/58 (2022.01); B60W 2554/4029 (2020.02); B60W 2554/4044 (2020.02); B60W 2556/35 (2020.02); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A processor comprising:
one or more circuits to:
receive first data representative of a plurality of outputs of a plurality of deep neural networks (DNNs), at least one output of the plurality of outputs corresponding to a respective sensor having a respective field of view different from fields of view corresponding to one or more others sensors of a plurality of sensors of an autonomous machine;
compute, using a fusion DNN and based at least in part on the first data, second data representative of a fusion of the plurality of outputs; and
perform one or more operations using the autonomous machine based at least in part on the second data.