Platform for document classification
First Claim
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1. A method, comprising:
- obtaining, by a processor, first information associated with a document,wherein the first information includes image data;
determining, for the document, by the processor, and using a first machine learning model, a first classification of one of a plurality of document types and a first confidence score associated with the first classification based on the image data,wherein the first confidence score indicates a first confidence level that the document corresponds to the first classification;
comparing, by the processor, the first confidence score and a first threshold value;
accepting, by the processor, the first classification of the document when the first confidence score satisfies the first threshold value;
obtaining, by the processor, second information associated with the document when the first confidence score fails to satisfy the first threshold value,wherein the second information includes text data;
determining, for the document, by the processor, and using a second machine learning model, a second classification of one of the plurality of document types and a second confidence score associated with the second classification based on the text data,wherein the second confidence score indicates a second confidence level that the document corresponds to the second classification;
comparing, by the processor, the second confidence score and a second threshold value; and
accepting, by the processor, the second classification of the document when the second confidence score satisfies the second threshold value.
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Abstract
A device obtains image data associated with a document. Using a first machine learning model, the device determines, for the document, a first classification of one of a plurality of document types and a first confidence score associated with the first classification, and a second classification of one of the plurality of document types and a second confidence score associated with the second classification based on the image data. The device determines a difference between the first confidence score and the second confidence score, compares the difference and a threshold value, and accept the first classification of the document when the difference satisfies the threshold value.
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Citations
20 Claims
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1. A method, comprising:
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obtaining, by a processor, first information associated with a document, wherein the first information includes image data; determining, for the document, by the processor, and using a first machine learning model, a first classification of one of a plurality of document types and a first confidence score associated with the first classification based on the image data, wherein the first confidence score indicates a first confidence level that the document corresponds to the first classification; comparing, by the processor, the first confidence score and a first threshold value; accepting, by the processor, the first classification of the document when the first confidence score satisfies the first threshold value; obtaining, by the processor, second information associated with the document when the first confidence score fails to satisfy the first threshold value, wherein the second information includes text data; determining, for the document, by the processor, and using a second machine learning model, a second classification of one of the plurality of document types and a second confidence score associated with the second classification based on the text data, wherein the second confidence score indicates a second confidence level that the document corresponds to the second classification; comparing, by the processor, the second confidence score and a second threshold value; and accepting, by the processor, the second classification of the document when the second confidence score satisfies the second threshold value. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A device, comprising:
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one or more memories; and one or more processors, communicatively coupled to the one or more memories, configured to; obtain image data associated with a document; determine, for the document and using a first machine learning model, a first classification of one of a plurality of document types and a first confidence score associated with the first classification, and a second classification of one of the plurality of document types and a second confidence score associated with the second classification based on the image data, wherein the first confidence score indicates a first confidence level that the document corresponds to the first classification, and the second confidence score indicates a second confidence level that the document corresponds to the second classification, wherein the first confidence score is greater than the second confidence score; determine a difference between the first confidence score and the second confidence score; compare the difference and a threshold value; and accept the first classification of the document when the difference satisfies the threshold value. - View Dependent Claims (10, 11, 12, 13, 14)
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15. A non-transitory computer-readable medium storing instructions, the instructions comprising:
one or more instructions that, when executed by one or more processors, cause the one or more processors to; receive first image data associated with a first page of a document; receive second image data associated with a second page of the document; determine, for the first page of the document and using a first machine learning model, a first classification of one of a plurality of document types and a first confidence score associated with the first classification based on the first image data, wherein the first confidence score indicates a first confidence level that the first page of the document corresponds to the first classification; determine, for the second page of the document and using the first machine learning model, a second classification of one of the plurality of document types and a second confidence score associated with the second classification based on the second image data, wherein the second confidence score indicates a second confidence level that the second page of the document corresponds to the second classification; compare the first confidence score and a first threshold value; compare the second confidence score and a second threshold value; accept the first classification of the first page of the document when the first confidence score satisfies the first threshold value; accept the second classification of the second page of the document when the second confidence score satisfies the second threshold value, wherein the one of the plurality of document types associated with the second classification is different than the one of the plurality of document types associated with the first classification; assign the first page of the document a first label corresponding to the first classification; assign the second page of the document a second label corresponding to the second classification; store the first label for access by a third-party device; and store the second label for access by the third-party device. - View Dependent Claims (16, 17, 18, 19, 20)
Specification