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. 17, 2023

Filed:

Nov. 01, 2022
Applicant:

Snap Inc., Santa Monica, CA (US);

Inventors:

Anup Prabhakar Dhalwani, Bronx, NY (US);

Walton Lin, Chatham, NJ (US);

Andrew Lin, Long Island City, NY (US);

Amer Shahnawaz, Venice, CA (US);

Leonid Gorkin, Chappaqua, NY (US);

Amber Taylor, Seattle, WA (US);

Lillian Zheng, Los Angeles, CA (US);

Eric Wood, Los Angeles, CA (US);

Assignee:

Snap Inc., Santa Monica, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/00 (2022.01); G06F 18/214 (2023.01); G06V 10/774 (2022.01); G06V 10/40 (2022.01); G01W 1/02 (2006.01); G06N 20/00 (2019.01); G06N 7/01 (2023.01);
U.S. Cl.
CPC ...
G01W 1/02 (2013.01); G06F 18/2148 (2023.01); G06N 7/01 (2023.01); G06N 20/00 (2019.01); G06V 10/40 (2022.01); G06V 10/7747 (2022.01); G06V 20/35 (2022.01); G06V 20/36 (2022.01); G06V 20/38 (2022.01);
Abstract

Systems and methods are provided for analyzing messages generated by a plurality of computing devices associated with a plurality of users in a messaging system to generate training data to train a machine learning model to determine a probability that a media content item was generated inside an enclosed location or outside, receiving a media content item from a computing device, analyzing the media content item using the trained machine learning model to determine a probability that the media content item was generated inside an enclosed location or outside, determining, based on the probability generated by the trained machine learning model, that the media content item was generated inside an enclosed location, and determining an inside temperature associated with the venue based on messages generated by a plurality of computing devices in a messaging system comprising media content items and temperature information for the venue or a similar venue type.


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