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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.

Patent No.:

US 12718517 B1

PDFFull Text
Date of Patent:
Aug. 25, 2026

Filed:

Jul. 11, 2022

Automated detection of chemical component of moving object

Applicant:

X Development Llc, Mountain View, CA (US);

Inventors:

Daniel Rosenfeld, Mountain View, CA (US);

Alexander Holiday, Brookfield, WI (US);

Gearoid Murphy, San Jose, CA (US);

Allen Richard Zhao, Mountain View, CA (US);

Hongxu MA, San Jose, CA (US);

Cyrus Behroozi, Menlo Park, CA (US);

Derek Werdenberg, Dublin, CA (US);

Jie Jacquot, San Carlos, CA (US);

Vadim Tschernezki, Mountain View, CA (US);

Assignee:

X Development LLC, Mountain View, CA (US);

Attorney:

Mughal Gaudry & Franklin PC

Primary Examiner:

Bobbak Safaipour

Assistant Examiner:

Ashley undefined Hytrek

Int. Cl.
CPC ...
G06V 10/58 (2022.01); B07C 5/342 (2006.01); G01N 21/84 (2006.01); G06V 10/143 (2022.01); G06V 10/147 (2022.01); G06V 10/26 (2022.01); G06V 10/60 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); H04N 23/11 (2023.01);
U.S. Cl.
CPC ...
G06V 10/58 (2022.01); B07C 5/342 (2013.01); G01N 21/84 (2013.01); G06V 10/143 (2022.01); G06V 10/147 (2022.01); G06V 10/26 (2022.01); G06V 10/60 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); H04N 23/11 (2023.01); B07C 2501/0054 (2013.01); G01N 2021/845 (2013.01);
Abstract

Image data is obtained that indicates an extent to which one or more objects reflect, scatter, or absorb light at each of multiple wavelength bands, where the image data was collected while a conveyor belt was moving the object(s). The image data is preprocessed by performing an analysis across frequencies and/or performing an analysis across a representation of a spatial dimension. A set of feature values is generated using the image preprocessed image data. A machine-learning model generates an output using to the feature values. A prediction of an identity of a chemical in the one or more objects or a level of one or more chemicals in the object(s) is generated using the output. Data is output indicating the prediction of the identity of the chemical in the object(s) or the level of the one or more chemicals in at least one of the one or more objects.

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