A method and system for segmenting touching text lines in an image of a uchen-script Tibetan historical document are provided. The method includes: first obtaining a binary image of a uchen-script Tibetan historical document after layout analysis; detecting local baselines in the binary image, to generate a local baseline information set; detecting and segmenting a touching region in the binary image according to the local baseline information set, to generate a touching-region-segmented image; allocating connected components in the touching-region-segmented image to corresponding lines, to generate a text line allocation result; and splitting text lines in the touching-region-segmented image according to the text line allocation result, to generate a line-segmented image. In the present disclosure, touching text lines in a Tibetan historical document can be effectively segmented, and text line segmentation efficiency of the Tibetan historical document is improved.

Systems, processes and methods for detecting rotated or angled text in an image based on global text geometry estimations are provided. A method includes, at an electronic device with memory and one or more processors, receiving an image including a plurality of pixels (802); determining, based on the image, one or more pixels of the plurality of pixels included in the image that contain text (804); identifying, based on the one or more pixels that contain text, a plurality of components in the image (810); determining a subset of components based on the plurality of components (814); determining, based on the pixels that contain text of the subset of components, one or more candidate text angles (816); determining a global text angle based on the determined one or more candidate text angles (824); and determining a first plurality of bounding boxes based on the global text angle (830).

Disclosed is an electronic apparatus. The electronic apparatus includes: a display, a memory storing at least one instruction, and a processor connected to the memory and the display and configured to control the electronic apparatus, the processor, by executing the at least one instruction, is configured to: based on receiving a command for adding a schedule being input while an image is displayed on the display, obtain a plurality of texts by performing text recognition of the image, obtain main datetime information corresponding to each of a plurality of pieces of schedule information and sub-datetime information corresponding to the main datetime information by causing the plurality of obtained texts to be provided to a first neural network model, and update schedule information of a user based on the obtained datetime information, and the first neural network model is configured to be trained to output main datetime information and sub-datetime information corresponding to the main datetime information based on receiving a plurality of pieces of datetime information.

A print job management apparatus includes a processor, and a storage device configured to store data of an expected result of a print job. The processor is configured to: read the data of the expected result from the storage device; obtain data of an actual result printed and output in accordance with the print job; and based on a result of comparison between the data of the expected result and the data of the actual result, obtain a processing status of the print job.

Systems and methods of image searching include receiving content, receiving a request to select an image from content, selecting a plurality of items in the image, retrieving information about the selected item, and providing display data based on the retrieved information.

Systems and methods of image searching include receiving content, receiving a request to select an image from content, selecting a plurality of items in the image, retrieving information about the selected item, and providing display data based on the retrieved information.

A method and system for performing on-device image to text conversion are provided. Embodiments herein relates to the field of performing image to text conversion and more particularly to performing on-device image to text conversion with an improved accuracy. A method performing on-device image to text conversion is provided. The method includes language detection from an image, understanding of text in an edited image and using a contextual and localized lexicon set for post optical character recognition (OCR) correction.

A method and system for performing on-device image to text conversion are provided. Embodiments herein relates to the field of performing image to text conversion and more particularly to performing on-device image to text conversion with an improved accuracy. A method performing on-device image to text conversion is provided. The method includes language detection from an image, understanding of text in an edited image and using a contextual and localized lexicon set for post optical character recognition (OCR) correction.

There is a need for more effective and efficient predictive data analysis solutions and/or more effective and efficient solutions for generating image representations of categorical data. In one example, embodiments comprise receiving a categorical input feature, generating an image representation of the categorical input feature, generating an image-based prediction based at least in part on the image representation, and performing one or more prediction-based actions based at least in part on the image-based prediction.

Introduced here are communication optimization platforms configured to improve comprehension, persuasion, or clarity of communications. Initially, a communication optimization platform can acquire input sample(s) that are associated with a source audience. The communication optimization platform can then create a linguistic profile for the source audience by examining the content of the input sample(s). Additionally or alternatively, the communication optimization platform may produce a psychographic profile that specifies various characteristics of the source audience, such as personality, opinions, attitudes, interests, etc. The communication optimization platform can then generate, based on the linguistic profile and/or the psychographic profile, affinity language for communicating with a target audience. By incorporating the affinity language into communications, the communication optimization platform can increase appeal to the target audience.