Extracting key information from document using trained machine-learning models

A system comprising:

• one or more processors;
• and
• a non-transitory computer-readable medium coupled to the one or more processors, the non-transitory computer-readable medium storing instructions executable by the one or more processors to cause the one or more processors to perform operations comprising:
• receiving a set of data within a document, the set of data including one or more key fields, wherein the data processing system comprises a table detection module, a key information extraction module, and a table extraction module;
• extracting text information and location data associated with the text information by performing an optical character recognition operation, the text information and the location data from the document;
• detecting, by the table detection module, whether one or more tables are present in the document, wherein the table detection module is a trained object detection neural network trainable using document images for outputting a plurality of pixel coordinates of one or more tables in the document images;
• for each of the one or more tables determined to be within the document, detecting, by the table detection module, a location of each of the one or more tables included in the document;
• extracting, by the key information extraction module and based on the text information and the location data, text from the one or more key fields;
• extracting, by the table extraction module, each of the one or more tables determined to be within the document based on:
• (i) text information and location data associated with the text information, and (ii) the location of each of the one or more tables;
• and
• outputting extraction results for the document, the extraction results including the text from the one or more key fields, and the one or more tables.

A non-transitory computer-readable medium storing instructions executable by one or more processors for causing the one or more processors to perform operations comprising:

• receiving a set of data within a document, the set of data including one or more key fields, wherein the data processing system comprises a table detection module, a key information extraction module, and a table extraction module;
• extracting text information and location data associated with the text information by performing an optical character recognition operation, the text information and the location data from the document;
• detecting, by the table detection module, whether one or more tables are present in the document, wherein the table detection module is a trained object detection neural network trainable using document images for outputting a plurality of pixel coordinates of one or more tables in the document images;
• for each of the one or more tables determined to be within the document, detecting, by the table detection module, a location of each of the one or more tables included in the document;
• extracting, by the key information extraction module and based on the text information and the location data, text from the one or more key fields;
• extracting, by the table extraction module, each of the one or more tables determined to be within the document based on:
• (i) text information and location data associated with the text information, and (ii) the location of each of the one or more tables;
• and
• outputting extraction results for the document, the extraction results including the text from the one or more key fields, and the one or more tables.