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:
Apr. 02, 2024

Filed:

Aug. 17, 2021
Applicant:

Maplebear Inc., San Francisco, CA (US);

Inventors:

Saurav Manchanda, Minneapolis, MN (US);

Krishnakumar Subramanian, Cupertino, CA (US);

Haixun Wang, Palo Alto, CA (US);

Min Xie, Santa Clara, CA (US);

Assignee:

Maplebear Inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 18/2411 (2023.01); G06F 18/214 (2023.01); G06F 18/22 (2023.01); G06N 3/084 (2023.01);
U.S. Cl.
CPC ...
G06F 18/2411 (2023.01); G06F 18/214 (2023.01); G06F 18/22 (2023.01); G06N 3/084 (2013.01);
Abstract

An online concierge system trains a classification model as a domain adversarial neural network from training data labeled with source classes from a source domain that do not overlap with target classes from a target domain output by the classification model. The online concierge system maps one or more source classes to a target class. The classification model extracts features from an image, classifies whether an image is from the source domain or the target domain, and predicts a target class for an image from the extracted features. The classification model includes a gradient reversal layer between feature extraction layers and the domain classifier that is used during training, so the feature extraction layers extract domain invariant features from an image.


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