A method for generating training data for hand-printed text recognition includes obtaining a structured document, obtaining a set of hand-printed character images and database metadata from a database, generating a modified document page image, and outputting a training file. The structured document includes a document page image that includes text characters and document metadata that associates each of the text characters to a document character label. The database metadata associates each of the set of hand-printed character images to a database character label. The modified document page image is generated by iteratively processing each of the text characters. The iterative processing includes determining whether an individual text character should be replaced, selecting a replacement hand-printed character image from the set of hand-printed character images, scaling the replacement hand-printed character image, and inserting the replacement hand-printed character image into the modified document page image.

A method for generating training data for hand-printed text recognition includes obtaining a structured document, obtaining a set of hand-printed character images and database metadata from a database, generating a modified document page image, and outputting a training file. The structured document includes a document page image that includes text characters and document metadata that associates each of the text characters to a document character label. The database metadata associates each of the set of hand-printed character images to a database character label. The modified document page image is generated by iteratively processing each of the text characters. The iterative processing includes determining whether an individual text character should be replaced, selecting a replacement hand-printed character image from the set of hand-printed character images, scaling the replacement hand-printed character image, and inserting the replacement hand-printed character image into the modified document page image.

Apparatuses, systems, methods, and computer program products are disclosed for data location mapping and extraction. A method displays a graphical user interface to a user on an electronic display screen for a computing device. A graphical user interface comprises user interface elements allowing the user to identify a plurality of locations within a first document. A method includes receiving user input based on the user interacting with the user interface elements of the graphical user interface to identify the plurality of locations within the first document. A method includes detecting a subsequent document. A method includes extracting data from the subsequent document based on the plurality of locations identified within the first document.

Disclosed herein are a text recognition method and apparatus based on hand interaction for AR glasses. The text recognition method based on hand interaction for AR glasses includes collecting RGB images, extracting hand joint information from the RGB images, generating a text image based on the hand joint information, recognizing text from the text image, and outputting the recognized text.

A determination device (10) includes: a reception unit (15a) that receives operation events; an estimation unit (15b) that estimates a determination criterion for determining identity of the operation events on the basis of an attribute value of an operation log included in the operation events; and a determination unit (15c) that determines identity for an operation event to be processed on the basis of the determination criterion.

Disclosed herein are a text recognition method and apparatus based on hand interaction for AR glasses. The text recognition method based on hand interaction for AR glasses includes collecting RGB images, extracting hand joint information from the RGB images, generating a text image based on the hand joint information, recognizing text from the text image, and outputting the recognized text.