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:
May. 25, 2021

Filed:

Jul. 12, 2019
Applicant:

Terraclear Inc., Bellevue, WA (US);

Inventors:

Brent Ronald Frei, Bellevue, WA (US);

Dwight Galen McMaster, Burien, WA (US);

Michael Racine, Bellevue, WA (US);

Jacobus du Preez, Snoqualmie, WA (US);

William David Dimmit, Seattle, WA (US);

Isabelle Butterfield, Bellevue, WA (US);

Clifford Holmgren, Spanaway, WA (US);

Dafydd Daniel Rhys-Jones, Tacoma, WA (US);

Thayne Kollmorgen, Eugene, OR (US);

Vivek Ullal Nayak, Seattle, WA (US);

Assignee:

TERRACLEAR INC., Bellevue, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06T 7/00 (2017.01); G08G 5/00 (2006.01); G06T 7/13 (2017.01); G06T 7/70 (2017.01); G05D 1/10 (2006.01); G06T 7/62 (2017.01); B64C 39/02 (2006.01); G06K 9/46 (2006.01); G06T 7/73 (2017.01); A01B 43/00 (2006.01); A01B 69/00 (2006.01); A01B 59/042 (2006.01); B64D 47/08 (2006.01); G05D 1/00 (2006.01); G06K 9/62 (2006.01); G06T 3/00 (2006.01); G06T 7/60 (2017.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0002 (2013.01); A01B 43/00 (2013.01); A01B 59/042 (2013.01); A01B 69/001 (2013.01); B64C 39/024 (2013.01); B64D 47/08 (2013.01); G05D 1/0038 (2013.01); G05D 1/101 (2013.01); G06K 9/0063 (2013.01); G06K 9/00657 (2013.01); G06K 9/00664 (2013.01); G06K 9/4604 (2013.01); G06K 9/6227 (2013.01); G06K 9/6228 (2013.01); G06K 9/6256 (2013.01); G06K 9/6261 (2013.01); G06K 9/6262 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06T 3/00 (2013.01); G06T 7/13 (2017.01); G06T 7/60 (2013.01); G06T 7/62 (2017.01); G06T 7/70 (2017.01); G06T 7/73 (2017.01); G08G 5/0034 (2013.01); G08G 5/0069 (2013.01); B64C 2201/123 (2013.01); B64C 2201/126 (2013.01); B64C 2201/127 (2013.01); B64C 2201/128 (2013.01); B64C 2201/146 (2013.01); G06T 2207/10032 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20104 (2013.01); G06T 2207/30188 (2013.01); G06T 2207/30244 (2013.01);
Abstract

An object identification method is disclosed. The method includes training a first neural network for a first set of conditions regarding a first plurality of objects, training a second neural network for a second set of conditions regarding a second plurality of objects, receiving a plurality of target images associated with a third set of conditions in which to identify objects, analyzing the plurality of target images using the first and second neural networks to identify objects in the plurality of target images resulting in object identification information, and selecting the first neural network or the second neural network as a preferred neural network for the third set of conditions based on an analysis of the object identification information.


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