In the case of learning a printed character region selected by a user, it is determined whether a handwritten character region is present near the printed character region. If it is determined that the handwritten character region is present near the printed character region, information about the handwritten character region present near the printed character region and information about another printed character region present near the printed character region are learned in association with information about the selected printed character region. This makes it possible to appropriately determine a circled character string and a character string selected with a check mark from among a plurality of options during a scanned image analysis.

An apparatus, system, and method, each of which associates a region subjected to image processing with identification information, receives, in response to a device accepting selection from a user, the identification information and image data from the device, and outputs a result of the image processing performed on the region subjected to image processing associated with the identification information.

A user may markup the training documents to identify salient terms in a set of training unstructured documents. The system may automatically generate an extraction ruleset for each salient term that can be manually modified or edited by the user. The user may also provide analysis rulesets for each of the salient terms using, for example, a no-code graphical user interface. A machine learning model can be trained to automatically extract and analyze the salient terms based on feature vectors built from the extraction rulesets and/or analysis rulesets of the salient terms. After training, the system may import a set of unstructured documents for term extraction and analysis by the trained machine learning model. The system may generate a report, such as a PDF or an interactive graphical user interface, summarizing the results of the extracted and analyzed salient terms.

Technology is described herein for facilitating a user's interaction with a digital ink document. The technology internally represents the ink document using a data structure having a hierarchy of nodes. The nodes describe respective elements in the ink document. The technology leverages the data structure to identify a set of nodes that grows upon the user's repeated selection of a particular part of the ink document. At each stage of the selection, the technology highlights a set of elements in the ink document that correspond to the current set of identified nodes. According to another illustrative aspect, the technology produces the data structure by modifying an original data structure provided by a text analysis engine. The technology performs this task with the objective of accommodating structured interaction by the user with the ink document.

A handwriting input device, in response to a handwriting operation that moves an object on an input surface with the object contacting the input surface, inputs information corresponding to the path of the contact position of the object on the input surface. The handwriting input device includes a sensor part and a determining part. The sensor part detects the contact position of the object on the input surface and the presence or absence of the object within a predetermined operation space adjacent to the input surface. The determining part determines the start and the end of the handwriting operation based on the detection result of the sensor part. The determining part determines the continuance of the handwriting operation in response to detecting the presence of the object within the operation space by the sensor part after determining the start of the handwriting operation.

Examples described herein include systems and methods for importing text into a draft email on a user device. In response to a user selecting the first selectable element, the user device can launch a camera interface on the display. The user can capture an image, such as a page of a book or newspaper, and then scale the captured image to the relevant desired portion. The example method can further include recognizing text within the scaled portion of the image and automatically importing the recognized text into the draft email. The user device can utilize a machine learning model to perform text recognition at the device and then insert the recognized text into the draft email automatically. The user device can also display an indication of the accuracy of the imported recognized text within the draft email.

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

According to one embodiment, an image reading device includes an image reading unit, a control unit, and an output unit. The image reading unit reads an image formed on a document to generate read image data. The control unit extracts at least one predetermined area from the read image data to generate extracted image data, compares the extracted image data and reference image data determined for each of the predetermined area, for each of the predetermined area, and generates an aggregated image obtained by aggregating the extracted image data and information indicating a result of the comparison. The output unit outputs the aggregated image.

Methods and systems for augmented key generation are described herein. A computing system may receive, from a first user device, an image of a keyboard of a second user device. The computing platform may detect, based on the image, a first missing key of the keyboard, and may generate an augmented version of the first missing key. The computing platform may send, to the first user device, the augmented version of the first missing key and commands directing the first user device to display the augmented version of the first missing key, which may cause the first user device to display the augmented version of the first missing key. Selection of the augmented version of the first missing key on the first user device may cause display of a character, corresponding to the first missing key, to be displayed at the second user device.

An information processing apparatus includes a processor configured to: read plural pieces of character string information written on a form; obtain feature information indicating a feature relating to an arithmetic operation in which numerical information included in the plural pieces of character string information is used and arrangement information indicating a positional relationship between the plural pieces of character string information; and define, on a basis of the feature information and the arrangement information, an arithmetic expression for performing an arithmetic operation using an operator relating to the plural pieces of character string information.