US 12,340,605 B2
Optical character recognition system with back propagation of an objective loss function
Taiwo Raphael Alabi, Berkeley, CA (US); Farzaneh Rajabi, Redwood City, CA (US); Ashwath Saran Mohan, San Ramon, CA (US); Devin Cabillo, Fairfield, CA (US); Jerome Levadoux, San Mateo, CA (US); and Nipun Dureja, Seattle, WA (US)
Assigned to Docusign, Inc., San Francisco, CA (US)
Filed by DocuSign, Inc., San Francisco, CA (US)
Filed on Jul. 27, 2022, as Appl. No. 17/874,688.
Prior Publication US 2024/0037970 A1, Feb. 1, 2024
Int. Cl. G06V 30/164 (2022.01); G06F 16/93 (2019.01); G06V 30/148 (2022.01)
CPC G06V 30/164 (2022.01) [G06F 16/93 (2019.01); G06V 30/153 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
accessing an image of a document comprising text;
processing the accessed image of the document to produce a first image version at a first resolution and to produce a second image version at a second resolution lower than the first resolution;
performing optical character recognition on the first image version to obtain a first set of text representative of the text of the document;
applying a machine-learned model to the second image version, the machine-learned model configured to produce a denoised image of the document at a third resolution, the third resolution higher than the second resolution;
performing optical character recognition on the denoised image of the document to obtain a second set of text representative of the text of the document;
generating a feature vector comprising entries each representative of a performance of the machine-learned model, at least one feature vector entry based on a comparison of the first set of text and the second set of text; and
retraining the machine-learned model using the generated feature vector.