Aspects of the present disclosure provide methods and apparatuses for processing a digital image of a document, for example, to determine whether the document is a long document. An exemplary method generally includes obtaining a plurality of digital images of the document, determining a type of the document, loading one or more pre-defined metrics associated with the document based on the determined type of the document, determining one or more characteristics of the document based on one or more analyses performed on the plurality of digital images of the document, comparing the one or more characteristics of the document with the one or more pre-defined metrics, and determining the document to be a long document based, at least in part, on the comparison.

Aspects of the present disclosure provide methods and apparatuses for processing a digital image of a document, for example, to determine whether the document is a long document. An exemplary method generally includes obtaining a plurality of digital images of the document, determining a type of the document, loading one or more pre-defined metrics associated with the document based on the determined type of the document, determining one or more characteristics of the document based on one or more analyses performed on the plurality of digital images of the document, comparing the one or more characteristics of the document with the one or more pre-defined metrics, and determining the document to be a long document based, at least in part, on the comparison.

A work assistance system includes a drawing, a work record table, a handwriting display determination unit, a display control unit, and input means. The drawing includes parts and handwritings. The work record table stores the handwriting for the part as the work record. The handwriting display determination unit determines, as the writing candidates, the handwritings not associated with the parts based on the work record table. The display control unit displays the writing candidates and the parts via the input means in a selectable manner on a data display unit of a terminal of a user.

According to one embodiment, a computer-implemented method is configured for building a classification and/or data extraction knowledge base using an electronic form. The method includes: receiving an electronic form having associated therewith a plurality of metadata labels, each metadata label corresponding to at least one element of interest represented within the electronic form; parsing the plurality of metadata labels to determine characteristic features of the element(s) of interest; building a representation of the electronic form based on the plurality of metadata labels; generating a plurality of permutations of the representation of the electronic form by applying a predetermined set of variations to the representation; and training either a classification model, an extraction model, or both using: the representation of the electronic form, and the plurality of permutations of the representation of the electronic form. Corresponding systems and computer program products are also disclosed.

A system for capturing a product tag image, extracting product information, and validating information. The extracted information is then utilized to populate a universal (brand independent) product registration database. To incentivize end users to register their new and in service products, entry is simplified by the use of an application on a smartphone, tablet or personal computer. A user downloads an application and enters their information then takes at least one picture/scan/image of the product label(s) that contain: 1) manufacturer name (and/or brand name), 2) model number, 3) serial number; and 4) date of production. Said information is extracted by Optical Character Recognition (OCR) and then validated before entering said database.

A system and method for identifying handwritten characters on an image using a classification model that employs a neural network. The system includes a computer having a processor and a memory device that stores data and executable code that, when executed, causes the processor to read and convert typed text on the image to machine encoded text to identify locations of the typed text on the image; identify a location on the image that includes handwritten text based on the location of predetermined typed text on the image; identify clusters of non-white pixels in the image at the location having the handwritten text; generate an individual and separate cluster image for each identified cluster; classify each cluster image using machine learning and at least one neural network to determine the likelihood that the cluster is a certain character; and determine what character each cluster image is based on the classification.

A method and system for using eye gaze tracking to extract information in textual form from documents is provided. The method includes: receiving an image that corresponds to a document; receiving, from an eye-tracking sensor configured to detect a sequence of eye-gaze positions on the document as a function of time, a sequence of measurements that correspond to a human reading of the document; determining, based on the received sequence of measurements, a region of the document that is being read by a human; and extracting the textual information that corresponds to the region.

The current modular implant is particularly useful in spinal surgical procedures. The modular implant can be provided with two anchors and a central section.

A system for capturing a product tag image, extracting product information, and validating information. The extracted information is then utilized to populate a universal (brand independent) product registration database. To incentivize end users to register their new and in service products, entry is simplified by the use of an application on a smartphone, tablet or personal computer. A user downloads an application and enters their information then takes at least one picture/scan/image of the product label(s) that contain: 1) manufacturer name (and/or brand name), 2) model number, 3) serial number; and 4) date of production. Said information is extracted by Optical Character Recognition (OCR) and then validated before entering said database.

The current modular implant is particularly useful in spinal surgical procedures. The modular implant can be provided with two anchors and a central section.