Intuit, Inc.

Preeti Duraipandian

Sricharan Kallur Palli Kumar

Peter Caton Anthony

Deepankar Mohapatra

Conrad De Peuter

Tharathorn Joy Rimchala

Efraim David Feinstein

Dominic Miguel Rossi

Thrathorn Rimchala

Fadoua Khmaissia

Surendra Maharjan

Hui Chen

A method may include extracting, from a document, a first key-value pair including a key and a first value and corresponding to a first confidence score, extracting a second key-value pair including the key and a second value corresponding to a second confidence score, classifying a first match probability for the first key-value pair and a second match probability for the second key-value pair, generating a first calibrated confidence score for the first confidence score and a second calibrated confidence score for the second confidence score by transforming, using precision lookup tables constructed from training records, the first match probability to the first calibrated confidence score and the second match probability to second calibrated confidence score, selecting, using the first and second calibrated confidence scores, one of the first key-value pair and the second key-value pair, and presenting, in a graphical user interface (GUI), the selected key-value pair.

Machine learning model-agnostic confidence calibration system and method

A method that includes extracting image features of a document image, executing an optical character recognition (OCR) engine on the document image to obtain OCR output, and extracting OCR features from the OCR output. The method further includes executing an anomaly detection model using features including the OCR features and the image features to generate anomaly score, and presenting anomaly score.

Multiple input machine learning framework for anomaly detection

A method of blank detection involves receiving a document from a user, where the document includes derived text; applying a trained blank detection model to the document to make a first prediction, where the first prediction indicates whether at least one field in the document is blank; comparing the first prediction with a second prediction, where the second prediction is made by an extraction model; and extracting the at least one field using the extraction model.

Detection of blanks in documents

Systems and methods are provided to determine consensus values for duplicate fields in a document or form.

Systems and methods for determining consensus values

Systems and methods that may be used to determine that input form field data is accurate or not, and associate a level of confidence with that determination. The systems and methods may use a multi part confidence model that uses inter-field correlation to tie the correctness of a particular field to the pattern of values seen in other fields of the document the field data is input from.

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Plano, TX, United States of America

Preeti Duraipandian