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:
Jul. 25, 2023

Filed:

Jul. 14, 2022
Applicant:

Adobe Inc., San Jose, CA (US);

Inventors:

Jayant Kumar, San Jose, CA (US);

Vera Lychagina, San Jose, CA (US);

Tarun Vashisth, New Delhi, IN;

Sudhakar Pandey, Sunnyvale, CA (US);

Sharad Mangalick, San Francisco, CA (US);

Rohith Mohan Dodle, Fremont, CA (US);

Peter Baust, Sunnyvale, CA (US);

Mina Doroudi, San Jose, CA (US);

Kerem Turgutlu, San Jose, CA (US);

Kannan Iyer, San Jose, CA (US);

Gaurav Kukal, Fremont, CA (US);

Archit Kalra, Fremont, CA (US);

Amine Ben Khalifa, San Jose, CA (US);

Assignee:

Adobe Inc., San Jose, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 20/00 (2022.01); G06F 16/53 (2019.01); G06N 3/08 (2023.01); G06F 18/23 (2023.01); G06F 18/214 (2023.01);
U.S. Cl.
CPC ...
G06V 20/35 (2022.01); G06F 16/53 (2019.01); G06F 18/214 (2023.01); G06F 18/23 (2023.01); G06N 3/08 (2013.01);
Abstract

Disclosed are systems and methods for dynamically determining categories for images. A computer-implemented method may include training a neural network to receive an input image and determine one or more image categories associated with the input image; obtaining a set of images associated with a user; determining, using the trained neural network, one or more image categories associated with each image included in the obtained set of images; determining one or more dominant image categories associated with the user based on the determined image categories for the obtained set of images; and determining an image editing user interface for the user based on the determined one or more dominant image categories.


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