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. 22, 2023

Filed:

Mar. 05, 2021
Applicant:

Omniearth, Inc., Arlington, VA (US);

Inventors:

Shadrian Strong, Bellevue, WA (US);

David Murr, Minneapolis, MN (US);

Lars P. Dyrud, Crownsville, MD (US);

Assignee:

OmniEarth, Inc., Arlington, VA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G06F 16/51 (2019.01); G06F 16/583 (2019.01); G06F 18/21 (2023.01); G06F 18/24 (2023.01); G06F 18/2413 (2023.01); G06N 3/045 (2023.01); G06V 30/19 (2022.01); G06V 30/24 (2022.01); G06V 10/82 (2022.01); G06V 20/10 (2022.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06F 16/51 (2019.01); G06F 16/5854 (2019.01); G06F 18/217 (2023.01); G06F 18/24 (2023.01); G06F 18/24143 (2023.01); G06N 3/045 (2023.01); G06V 10/82 (2022.01); G06V 20/176 (2022.01); G06V 30/19173 (2022.01); G06V 30/2504 (2022.01);
Abstract

Methods and systems for automatic estimation of object characteristics from a digital image are disclosed, including a method comprising sub-dividing into two or more segments a digital image comprising pixels and depicting an object of interest, wherein each segment comprises two or more pixels; assessing content depicted in one or more of the segments for a predetermined object characteristic using machine learning techniques comprising General Image Classification of the one or more segments using a convolutional neural network, wherein the General Image Classification comprises analyzing the segment as a whole and outputting a general classification for the segment as a whole as related to the one or more predetermined object characteristic; and determining a level of confidence of one or more of the segments having the one or more predetermined object characteristic based on the General Image Classification assessment.


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