A display device includes a circuitry configured to perform a search for a plurality of image candidates in an image transformation dictionary part, based on handwritten data, and a display configured to display the plurality of image candidates obtained by the search. At least a portion of the plurality of image candidates displayed on the display represents a different person or an object.

Examples described herein generally relate to systems and methods for handwriting recognition. In an example, a computing device may receive input corresponding to a handwritten word and apply first recognition model to the input. The first recognition model may be configured to determine a first confidence level of a first portion of the input is greater than a second confidence level of a second portion of the input. The computing device may also apply a second recognition model to the input, wherein the second recognition model is different from the first recognition model and combine results of the first recognition model and the second recognition model to determine a list of candidate words. The computing device may also output one or more candidate words from the list of candidate words.

Examples described herein generally relate to systems and methods for handwriting recognition. In an example, a computing device may receive input corresponding to a handwritten word and apply first recognition model to the input. The first recognition model may be configured to determine a first confidence level of a first portion of the input is greater than a second confidence level of a second portion of the input. The computing device may also apply a second recognition model to the input, wherein the second recognition model is different from the first recognition model and combine results of the first recognition model and the second recognition model to determine a list of candidate words. The computing device may also output one or more candidate words from the list of candidate words.

An object is to provide a display apparatus capable of identifying handwritten data drawn by a particular display apparatus. A display apparatus for displaying data, in which indication of handwritten input originated data drawn by the display apparatus is recorded in association with the handwritten data.

An object is to provide a display apparatus capable of identifying handwritten data drawn by a particular display apparatus. A display apparatus for displaying data, in which indication of handwritten input originated data drawn by the display apparatus is recorded in association with the handwritten data.

The present disclosure is generally directed to systems and methods for executing optical character recognition faster than at least some traditional OCR systems, without sacrificing recognition accuracy. Towards this end, various exemplary embodiments involve the use of a bounding box and a grid-based template to identify certain unique aspects of each of various characters and/or numerals. For example, in one embodiment, the grid-based template can be used to recognize a numeral and/or a character based on a difference in centerline height between the numeral and the character when a monospaced font is used. In another exemplary embodiment, the grid-based template can be used to recognize an individual digit among a plurality of digits based on certain parts of the individual digit being uniquely located in specific portions of the grid-based template.

Digital handwriting synthesis techniques and systems are described that are configured to process text represented using text fields into one or more digital ink strokes to represent the text as handwritten data when rendered in a user interface of a computing device. Additionally, the digital handwriting synthesis techniques are configurable using normalization parameters to adjust an output from a machine learning model such that these techniques are extensible across a wide range of machine learning models and may be used to support a wide range of different digital ink styles. Further, the techniques described herein also support customization via “few shot conditioning” in which the digital ink styles may be further customized based on a user input and in this way support previously unseen digital ink styles.

Digital handwriting synthesis techniques and systems are described that are configured to process text represented using text fields into one or more digital ink strokes to represent the text as handwritten data when rendered in a user interface of a computing device. Additionally, the digital handwriting synthesis techniques are configurable using normalization parameters to adjust an output from a machine learning model such that these techniques are extensible across a wide range of machine learning models and may be used to support a wide range of different digital ink styles. Further, the techniques described herein also support customization via “few shot conditioning” in which the digital ink styles may be further customized based on a user input and in this way support previously unseen digital ink styles.

Examples described herein generally relate to rendering grid-aligned digital ink on a display of a computing device. In an example, the computing device determines grid pattern data associated with a grid pattern displayed on the display and a velocity of the input. Based the grid line pattern data and the velocity, the computing device may render digital ink that is traced along one or more grid lines of the grid pattern.

Examples described herein generally relate to rendering grid-aligned digital ink on a display of a computing device. In an example, the computing device determines grid pattern data associated with a grid pattern displayed on the display and a velocity of the input. Based the grid line pattern data and the velocity, the computing device may render digital ink that is traced along one or more grid lines of the grid pattern.