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:
Dec. 03, 2024

Filed:

Nov. 14, 2019
Applicant:

Servicenow Canada Inc., Montréal, CA;

Inventors:

Perouz Taslakian, Montreal, CA;

Negin Sokhandan Asl, Montreal, CA;

Assignee:

ServiceNow Canada Inc., Montreal, CA;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/82 (2022.01); G06F 16/538 (2019.01); G06F 16/583 (2019.01); G06V 20/62 (2022.01); G06V 30/10 (2022.01); G06V 30/14 (2022.01); G06V 30/148 (2022.01); G06V 30/19 (2022.01); G06V 30/262 (2022.01);
U.S. Cl.
CPC ...
G06V 10/82 (2022.01); G06F 16/538 (2019.01); G06F 16/5846 (2019.01); G06V 20/62 (2022.01); G06V 30/1444 (2022.01); G06V 30/153 (2022.01); G06V 30/19173 (2022.01); G06V 30/262 (2022.01); G06V 30/10 (2022.01);
Abstract

Systems and methods for detecting and predicting text within images. An image is passed to a feature-extraction module. Each image typically contains at least one text object, and each text object contains at least one character. Based on the image, the feature-extraction module generates at least one feature map indicating text object(s) in the image. The feature map(s) is then passed to a decoder module. In son implementations, the decoder module applies a weighted mask to the feature map(s). Based on the feature map(s), the decoder module predicts a sequence of characters in the text object(s). In some embodiments, that prediction is based on previous known data. The decoder module is directed by a query that indicates at least one desired characteristic of the text object(s). An output module then refines the predicted content. At least one neural network may be used.


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