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. 05, 2025

Filed:

Dec. 02, 2021
Applicant:

Quantarium Group, Llc, Redmond, WA (US);

Inventors:

Vignesh Ram Nithin Kappagantula, Kirkland, WA (US);

Andrei Aron, Woodinville, WA (US);

Dominic Suciu, Edmonds, WA (US);

Mihai Petriuc, Redmond, WA (US);

John Smintina, Kirkland, WA (US);

Clement Ifrim, Sammamish, WA (US);

Malcolm Cannon, Seattle, WA (US);

Petru Cociorva, Redmond, WA (US);

Adrian Fanaru, Sammamish, WA (US);

Assignee:

Quantarium Group, LLC, Redmond, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06F 18/214 (2023.01); G06N 3/045 (2023.01); G06Q 50/16 (2012.01); G06T 7/11 (2017.01); G06V 10/42 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/10 (2022.01); G06V 20/70 (2022.01);
U.S. Cl.
CPC ...
G06V 10/764 (2022.01); G06F 18/214 (2023.01); G06N 3/045 (2023.01); G06Q 50/16 (2013.01); G06T 7/11 (2017.01); G06V 10/42 (2022.01); G06V 10/82 (2022.01); G06V 20/176 (2022.01); G06V 20/70 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20132 (2013.01);
Abstract

Systems and methods are disclosed for computer vision property evaluation. In certain embodiments, a method may comprise executing a computer vision property evaluation operation via a computing system. The computer vision property evaluation operation may include identifying an image of a selected property feature using a first neural network (NN) of the computing system, cropping the image of the selected property feature in a selected way to produce a cropped image using a second NN of the computing system, generating a categorization of the cropped image based on identified details of the selected property feature, and generating a classification of a property corresponding to the selected property feature based on the categorization.


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