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:
Aug. 01, 2023

Filed:

Jan. 28, 2021
Applicant:

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

Inventors:

Naghmeh Rezaei, Redwood City, CA (US);

Pedro Miguel Filipe Cruz, San Diego, CA (US);

Assignee:

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

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06T 5/20 (2006.01); G06N 20/20 (2019.01); G06N 5/04 (2023.01); G16B 25/00 (2019.01); G06F 18/2433 (2023.01); G06F 18/214 (2023.01); G06F 18/21 (2023.01); G06F 18/243 (2023.01); G06N 5/01 (2023.01); G06V 10/56 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 10/98 (2022.01); G06V 20/69 (2022.01); G01N 21/64 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06F 18/2148 (2023.01); G06F 18/2163 (2023.01); G06F 18/2433 (2023.01); G06F 18/24323 (2023.01); G06N 5/01 (2023.01); G06N 5/04 (2013.01); G06N 20/20 (2019.01); G06T 5/20 (2013.01); G06V 10/56 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/7715 (2022.01); G06V 10/993 (2022.01); G06V 20/698 (2022.01); G16B 25/00 (2019.02); G01N 21/6428 (2013.01); G01N 2021/6439 (2013.01); G06T 2207/10064 (2013.01); G06T 2207/20028 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20192 (2013.01); G06T 2207/30072 (2013.01); G06T 2207/30168 (2013.01);
Abstract

The technology disclosed relates to classification of process cycle images to predict success or failure of process cycles. The technology disclosed includes capturing and processing images of sections arranged on an image generating chip in genotyping process. Image description features of production cycle images are created and given as input to classifiers. A trained classifier separates successful production images from unsuccessful or failed production images. The failed production images are further classified by a trained root cause classifier into various categories of failure.


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Quick Actions:

Rezaei, Naghmeh. (2023). Machine learning-based root cause analysis of process cycle images (U.S. Patent No. 11715200). U.S. Patent and Trademark Office. https://idiyas.com/patent/badge/11715200

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