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:
Oct. 29, 2024

Filed:

Jan. 07, 2022
Applicant:

Schlumberger Technology Corporation, Sugar Land, TX (US);

Inventors:

Tetsushi Yamada, Cambridge, MA (US);

Simone Di Santo, Dhahran, SA;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06V 10/82 (2022.01); E21B 44/00 (2006.01); G01N 15/1433 (2024.01); G06N 3/08 (2023.01); G06T 7/00 (2017.01); G06T 7/73 (2017.01); G06V 10/77 (2022.01); G06V 10/774 (2022.01); G06V 20/10 (2022.01);
U.S. Cl.
CPC ...
G06V 10/82 (2022.01); E21B 44/00 (2013.01); G06N 3/08 (2013.01); G06T 7/0004 (2013.01); G06T 7/74 (2017.01); G06V 10/7715 (2022.01); G06V 10/774 (2022.01); G06V 20/10 (2022.01); E21B 2200/22 (2020.05); G01N 15/1433 (2024.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30181 (2013.01);
Abstract

Systems and methods presented herein are configured to train a neural network model using a first set of photographs, wherein each photograph of the first set of photographs depicts a first set of objects and include one or more annotations relating to each object of the first set of objects; to automatically create mask images corresponding to a second set of objects depicted by a second set of photographs; to enable manual fine tuning of the mask images; to re-train the neural network model using the second set of photographs, wherein the re-training is based at least in part on the manual fine tuning of the mask images; and to identify one or more individual objects in a third set of photographs using the re-trained neural network model.


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