A method for processing lists in handwriting, comprising: initially classifying each of a plurality of text lines as a distinct text item which is not part of a list; and a classification process comprising a pattern detection in each text line for classifying each text line starting with a predetermined list symbol as a distinct list item which is part of a list; determining an item indentation of each text item with respect to a reference position and determining for each list item a text indentation representing the indentation of text comprised in said list item; and a merging step for merging, as part of a same text item, or as part of a same list item, if predefined conditions are met. A text structure data model may then be generated based on a result of the merging process.

A method for processing lists in handwriting, comprising: initially classifying each of a plurality of text lines as a distinct text item which is not part of a list; and a classification process comprising a pattern detection in each text line for classifying each text line starting with a predetermined list symbol as a distinct list item which is part of a list; determining an item indentation of each text item with respect to a reference position and determining for each list item a text indentation representing the indentation of text comprised in said list item; and a merging step for merging, as part of a same text item, or as part of a same list item, if predefined conditions are met. A text structure data model may then be generated based on a result of the merging process.

A computer-implemented method of generating electronic documents is described. The method comprises receiving a plurality of scanned documents for a plurality of vehicles; providing the plurality of scanned documents to a neural network model that outputs respective class identifiers of the plurality of scanned documents; for each scanned document of the plurality of scanned documents, extracting data from the scanned document according to a corresponding class identifier, and associating the scanned document and the extracted data with an identified vehicle of the plurality of vehicles, wherein the identified vehicle is identified by the extracted data; and generating an electronic document for the identified vehicle using the extracted data.

A method and a system for converting a font of a Chinese character in an image, a computer device and a medium are disclosed. A specific implementation of the method includes: acquiring a stroke of a to-be-converted Chinese character in the image and spatial distribution information of the stroke; and generating a Chinese character in a target font that corresponds to the to-be-converted Chinese character in the image according to the stroke of the to-be-converted Chinese character, the spatial distribution information of the stroke and standard stroke information of the target font, to replace the to-be-converted Chinese character.

A system includes a training system configured to display first image data and a remote expert system configured to display second image data that corresponds to the first image data, receive feedback data associated with the second image data, and transmit a command to the training system based on the feedback data. The command is configured to modify the first image data presented via the training system.

One variation of a method includes: accessing a handwriting sample comprising a set of user glyphs handwritten by a user; for each character in a set of characters, identifying a subset of user glyphs corresponding to the character in the handwriting sample, characterizing variability of a set of spatial features across the subset of user glyphs, and storing variability of the set of spatial features across the subset of user glyphs in a character container corresponding to the character; and compiling the set of character containers into a handwriting model for the user. The method further includes: accessing a text string comprising a combination of characters in the set of characters; for each instance of each character in the text string, inserting a set of variability parameters into the handwriting model to generate a synthetic glyph representing the character; and assembling the set of synthetic glyphs into a print file.

Ink-processing technology is set forth herein for detecting a gesture that a user performs in the course of interacting with an ink document. The technology operates by identifying a grouping of ink strokes created by the user. The technology then determines whether the grouping expresses a gesture based on a combination of spatial information and image information, both of which describe the grouping. That is, the spatial information describes a sequence of positions traversed by the user in drawing the grouping of ink strokes using an ink capture device, while the image information refers to image content in an image produced by rendering the grouping into image form. The technology also provides a technique for identifying the grouping by successively expanding a region of analysis, to ultimately provide a spatial cluster of ink strokes for analysis.

Ink-processing technology is set forth herein for detecting a gesture that a user performs in the course of interacting with an ink document. The technology operates by identifying a grouping of ink strokes created by the user. The technology then determines whether the grouping expresses a gesture based on a combination of spatial information and image information, both of which describe the grouping. That is, the spatial information describes a sequence of positions traversed by the user in drawing the grouping of ink strokes using an ink capture device, while the image information refers to image content in an image produced by rendering the grouping into image form. The technology also provides a technique for identifying the grouping by successively expanding a region of analysis, to ultimately provide a spatial cluster of ink strokes for analysis.

Provided is an input system including an instruction device; a detection device that detects an instruction position of the instruction device; a display device that is provided separately from the detection device and that displays an image of a space; a position detector that detects, in the space, a line-of-sight position in a line-of-sight of the position detector; a processor; and a memory storing instructions, which when executed by the processor, cause the processor to set, in the space, an instruction target area including a reference position of the instruction device, based on the line-of-sight position detected by the position detector at the time of reception of a predetermined operation by the instruction device, and control the display device to display the instruction position of the instruction device in the instruction target area and on the image of the space.

A handwriting processing method, a touch display device, a computer device, and a storage medium are provided. The handwriting processing method includes: determining, according to a sample point in a writing track that is input by a user by means of a touch display, a group of track points and a related parameter of each track point, the related parameter including a coordinate parameter and a time parameter; determining, according to the related parameter of each track point, a start position, an end position, and a type of a stroke contained in the writing track, where the type of the stroke includes one of a horizontal stroke, a vertical stroke, a left-falling stroke, a right-falling stroke or a lifting stroke; and determining, according to the type of the stroke, a shape of the start position of the stroke.