Automatic key/value pair extraction from document images using deep learning

A computerized method for identifying keyword strings and associated values from a document image, comprising:

• receiving the document image from a document storage, wherein the document image comprises a plurality of pixels and wherein each pixel within the document image is represented by a plurality of bits contained in a computer system storage;
• modifying the document image, from a first version of the document image to a second version of the document image;
• allocating for each pixel of the plurality of pixels, a first subset of bits representing information corresponding to the second version of the document image;
• and
• allocating for each pixel, a second subset of bits wherein the second subset of bits does not overlap with the first subset of bits, and setting the value of each bit within the second subset of bits for each pixel, to represent the second version of the document image in a manner selected to facilitate recognition of textually encoded segments within the document image by a deep neural network trained to recognize objects within an image;
• detecting by the deep neural network, groupings of text segments in the document image, wherein each grouping of text segments in the document image is associated with a spatial template;
• and
• mapping the text segments in the groupings of text segments in the document image to known string values to identify the keyword strings and associated values, wherein the keyword string is representative of semantic meaning of a grouping of text segments.