Synthetic image generation using artificial intelligence

A system comprising:

• at least one processor, and
• at least one non-transitory storage media storing instructions that, when executed by the at least one processor, cause the at least one processor to:
• obtain a captured image of a symbol of a symbology type that encodes data;
• produce a synthetic image from the captured image using a trained machine learning model,
• wherein the trained machine learning model has been trained using (i) first images of examples of symbols of the symbology type, and (ii) second images of the examples of symbols of the symbology type,
• wherein the first images have a first image quality, the second images have a second image quality that is different than the first image quality, and
• wherein one or more parameters of the machine learning model have been adjusted responsive to one or more image features to tradeoff content loss versus style loss using measurements of information content correlation between third images produced during training and each of the first images and the second images, the measurements being from a comparison metric associated with the symbology type;
• and
• provide the synthetic image produced by the trained machine learning model for use by a program configured to identify information in images of symbols of the symbology type.