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:
Sep. 02, 2025

Filed:

Jul. 15, 2024
Applicant:

Nearmap Us, Inc., Lehi, UT (US);

Inventors:

Julius Simonelli, San Diego, CA (US);

Ilsoo Seong, Aliso Viejo, CA (US);

Jason Janofsky, San Marcos, CA (US);

Nicholas Molyneux, San Diego, CA (US);

David Tobias, San Francisco, CA (US);

David Lyman, Houston, TX (US);

Assignee:

NEARMAP US, INC., Lehi, UT (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/00 (2022.01); G06T 7/00 (2017.01); G06V 10/24 (2022.01); G06V 10/26 (2022.01); G06V 10/32 (2022.01); G06V 10/82 (2022.01); G06V 20/10 (2022.01);
U.S. Cl.
CPC ...
G06V 20/176 (2022.01); G06T 7/0002 (2013.01); G06V 10/245 (2022.01); G06V 10/26 (2022.01); G06V 10/32 (2022.01); G06V 10/82 (2022.01); G06T 2200/24 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30184 (2013.01);
Abstract

Methods, non-transitory computer readable media, and roof analysis systems are disclosed that preprocess overhead images in imagery data obtained based on a request comprising a geographic location. The overhead images depict a building at different historical points in time identified in the imagery data. A neural network is applied to input data structures into which the overhead images are converted. The neural network is trained to extract relationships between features from the input data structures indicating changes in a roof of the building and generate an output data structure representing the changes. Patterns in the output data structure are analyzed to determine instances of change of the roof. A roof age is then output via a user interface in response to the request. The roof age is generated based on a likelihood of the instances of change or a time interval between the overhead images and a current time.


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