Methods and an apparatuses for recognizing a text, recognition devices and storage media are provided, which belong to the field of text detections. A method includes: extracting, by the recognition device, a feature map of a to-be-recognized image, then determining segmentation information of a text region of the to-be-recognized image based on a preset segmentation network and the feature map, and then determining boundary key points in the text region based on the segmentation information, and then converting a text in the text region into a text with a target arrangement sequence based on the boundary key points and then inputting the text obtained by conversion into a preset recognition model for recognition processing.

Methods and an apparatuses for recognizing a text, recognition devices and storage media are provided, which belong to the field of text detections. A method includes: extracting, by the recognition device, a feature map of a to-be-recognized image, then determining segmentation information of a text region of the to-be-recognized image based on a preset segmentation network and the feature map, and then determining boundary key points in the text region based on the segmentation information, and then converting a text in the text region into a text with a target arrangement sequence based on the boundary key points and then inputting the text obtained by conversion into a preset recognition model for recognition processing.

According to an embodiment, the information processing apparatus includes an image interface, an input interface, a communication interface, and a processor. The image interface is configured to acquire a display screen image from an input device for inputting a character string included in a captured image in which recognition of the character string according to a first algorithm fails. The processor is configured to search for the captured image corresponding to the display screen image, acquire the character string based on a result of character recognition processing of the searched for captured image according to a second algorithm, and input the character string to the input device.

The present disclosure provides an image processing method, a text recognition method and an apparatus. The image processing method includes: preprocessing acquired sample images to obtain position information, image blocks and text content corresponding to fields in the sample images respectively; making a mask prediction on the position information of the fields according to the position information, the image blocks and the text content corresponding to the fields respectively to obtain a prediction result; and training according to the prediction result to obtain a text recognition model, where the text recognition model is used to perform text recognition on a to-be-recognized image.

A method includes executing a Optical Character Recognition (OCR) preprocessor on training images to obtain OCR preprocessor output, executing an OCR engine on the OCR preprocessor output to obtain OCR engine output, and executing an approximator on the OCR preprocessor output to obtain approximator output. The method further includes iteratively adjusting the approximator to simulate the OCR engine using the OCR engine output and the approximator output, and generating OCR preprocessor losses using the approximator output and target labels. The method further includes iteratively adjusting the OCR preprocessor using the OCR preprocessor losses to obtain a customized OCR preprocessor.

A computer-implemented method, a device, and a non-transitory computer-readable storage medium of automatically determining an interactive GUI element in a graphic user interface (GUI) to be interacted. The method includes: detecting, by the processor, one or more candidate interactive GUI elements in the GUI based on a plurality of algorithms; determining, by the processor, a likelihood indicator for each of the one or more candidate interactive GUI elements, a likelihood indicator indicating the likelihood that a candidate interactive GUI element associated with the likelihood indicator is an interactive GUI element to be interacted; and determining, by the processor, an interactive GUI element to be interacted from the one or more candidate interactive GUI elements based on the likelihood indicators.

Systems and methods disclosed herein provide context-based application suggestions to a user in real time. A user device can identify a keyword displayed in an application, such as an email application. The user device can request a card from a connector external to the user device. The connector can identify an application that relates to the keyword and determine a current installation status for the application with respect to the user device. The connector can query a management server at which the user device is enrolled to request the installation status. If the application is not installed on the user device, the connector can instruct the user device to prompt the user to install the application. If the application is installed, the connector can instruct the user device to prompt the user to launch the installed application.

A method and computer programs for detecting document regions that will be excluded from a watermark embedding process are disclosed. The method comprises converting, by an adapter module, at least one page of a received document into a visual representation thereof, the visual representation keeping the position of the characters of the at least one page; receiving, by a text detector, the visual representation; processing, by the text detector, the visual representation using one or more artificial intelligence algorithms, and returning a list of invalid regions with their associated page positions as a result, wherein each invalid region of the list of invalid regions may have associated thereto a confidence score; and using, by a watermark embedding module or by a watermark extracting module, the list of invalid regions to provide a watermarked document or a message embedded in the document.

A method and computer programs for detecting document regions that will be excluded from a watermark embedding process are disclosed. The method comprises converting, by an adapter module, at least one page of a received document into a visual representation thereof, the visual representation keeping the position of the characters of the at least one page; receiving, by a text detector, the visual representation; processing, by the text detector, the visual representation using one or more artificial intelligence algorithms, and returning a list of invalid regions with their associated page positions as a result, wherein each invalid region of the list of invalid regions may have associated thereto a confidence score; and using, by a watermark embedding module or by a watermark extracting module, the list of invalid regions to provide a watermarked document or a message embedded in the document.

The present disclosure provides a training method and apparatus for a document processing model, a device, a storage medium and a program, which relate to the field of artificial intelligence, and in particular, to technologies such as deep learning, natural language processing and text recognition. The specific implementation is: acquiring a first sample document; determining element features of a plurality of document elements in the first sample document and positions corresponding to M position types of each document element according to the first sample document; where the document element corresponds to a character or a document area in the first sample document; and performing training on a basic model according to the element features of the plurality of document elements and the positions corresponding to the M position types of each document element to obtain the document processing model.