Reliable determination of field values in documents with removal of static field elements

A method of training a machine learning model (MLM), the method comprising:

• obtaining a first training image of a field, wherein the first training image depicts one or more static elements of the field and a first field value;
• obtaining one or more additional training images of the field;
• causing the MLM to concurrently process the first training image and the one or more additional training images to generate a training output that classifies at least some of a plurality of units of the first training image as one of at least:
• a unit associated with the one or more static elements of the field, or
• a unit associated with the first field value;
• adjusting parameters of the MLM based on the training output;
• and
• causing the trained MLM to be deployed to determine one or more field values in at least one additional document.

A system comprising:

• a memory;
• and
• a processing device communicatively coupled to the memory, the processing device to:
• obtain an input into a machine learning model (MLM), wherein the input comprises:
• a first image of a field, wherein the first image is extracted from a first document and depicts one or more static elements of the field and a first field value, and
• a second image of the field;
• process the input using the MLM to identify one or more static regions, wherein each of the one or more static regions corresponds to at least one of the one or more static elements of the field;
• generate a modified first image of the field, wherein the modified first image depicts at least one of the one or more static regions with a reduced visibility compared with the first image;
• and
• determine the first field value using the modified first image.