The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Feb. 08, 2022

Filed:

Oct. 05, 2018
Applicant:

Netradyne, Inc., San Diego, CA (US);

Inventors:

Michael Campos, La Jolla, CA (US);

Venkata Sreekanta Reddy Annapureddy, San Diego, CA (US);

David Jonathan Julian, San Diego, CA (US);

Veeresh Taranalli, San Diego, CA (US);

Jonathan Albert Cox, Imperial Beach, CA (US);

Arvind Yedla, La Jolla, CA (US);

Assignee:

NETRADYNE, INC., San Diego, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06K 9/62 (2006.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); H04N 5/225 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00798 (2013.01); G06K 9/6256 (2013.01); G06K 9/6262 (2013.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); H04N 5/2253 (2013.01);
Abstract

A neural network is configured to process image data captured by a vehicle-mounted camera. The neural network includes common processing layers (a trunk) and separate, parallelizable processing layers (branches). An object detection branch of the neural network is trained to detect objects that may be visible from the vehicle-mounted camera, such as cars, trucks, and traffic signs. A curve determination branch is trained to detect and parameterize salient curves, such as lane boundaries and road boundaries. The curve determination branch itself is configured with a trunk and branch architecture, having both common and separate processing layers. A first branch computes a likelihood that a curve is present in a given location of the image data and a second branch further localizes the curve within the given location if such a curve is present. Training of the different branches of the neural network may be decoupled.


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