A method and a platform of generating a document, an electronic device, and a storage medium are provided, which relate to a field of an artificial intelligence technology, in particular to fields of computer vision and deep learning technologies, and may be applied to a text recognition scenario and other scenarios. The method includes: performing a category recognition on a document picture to obtain a target category result; determining a target structured model matched with the target category result; and performing, by using the target structured model, a structure recognition on the document picture to obtain a structure recognition result, so as to generate an electronic document based on the structure recognition result, wherein the structure recognition result includes a field attribute recognition result and a field position recognition result.

The present disclosure relates to a system and computer-implemented method for character recognition in a payment card. The method includes receiving an image of a payment card and one or more details associated with the payment card. Further, a derivative of the image is determined based on the one or more details and a horizontal sum of pixel values is determined for a plurality of rows in the image. Furthermore, one or more Regions of Interest (ROIs) are identified in the image by comparing the horizontal sum of pixel values with a predefined first threshold. Subsequently, one or more characters in the one or more ROIs are extracted using one or more peak values in a histogram of the one or more ROIs. Finally, each of the one or more characters extracted from the one or more ROIs is recognized using a trained Artificial Intelligence technique.

A character recognition method includes inputting an input image of a document, with the input image including a plurality of characters; selecting the plurality of characters through an object detection module to form at least one character region; separating the plurality of characters in the at least one character region to form a plurality of character boxes; performing calculation to determine a format of a character in each of the plurality of character boxes; recognizing the characters in the at least one character region through an object recognition module to determine a symbol content of the character in each of the plurality of character boxes; and converting the plurality of characters according to the format and symbol content of the character in each of the plurality of character boxes, and outputting corresponding editable characters.

A method and an apparatus for recognizing a subtitle region, a device, and a storage medium are provided, relating to the field of computer vision technologies of artificial intelligence. The method includes: recognizing a video to obtain n candidate subtitle regions, the candidate subtitle regions being regions in which text contents are displayed in the video, and n being a positive integer; and screening the n candidate subtitle regions according to a subtitle region screening policy to obtain the subtitle region, the subtitle region screening policy being used for determining a candidate subtitle region in which text contents have a repetition rate being lower than a repetition rate threshold and have a longest total display duration as the subtitle region. By using the method and apparatus, device, and system, labor resources required for subtitle region recognition can be saved.

A system for capturing images during production of printed material includes an optical device comprising a plurality of cameras arranged in an array with adjacent pairs of cameras having overlapping fields of view. An imaging controller device determines a layout of content on printed material, and determines, based on the layout, an optical system configuration profile. Determining the optical system configuration profile includes selecting one or more cameras for capturing images of regions of interest on the printed material and determining a trigger interval for triggering the selected one or more cameras. The imaging controller device triggers the selected cameras at times determined based on the trigger interval to capture images of the regions of interest on the printed material as the printed material moves in fields of view of the one or more cameras during production of the printed material.

A device includes a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of loading a user profile for a user consuming undigitized, static media content; identifying an area of interest in the undigitized, static media content; analyzing the area of interest; responsive to the user profile, creating immersive content to enhance the area of interest; and providing the immersive content for presentation to the user.

This application provides a method for detecting images of testing object using hyperspectral imaging. Firstly, obtaining a hyperspectral imaging information according to a reference image, hereby, obtaining corresponded hyperspectral image from an input image and obtaining corresponded feature values for operating Principal components analysis to simplify feature values. Then, obtaining feature images by Convolution kernel, and then positioning an image of an object under detected by a default box and a boundary box from the feature image. By Comparing with the esophageal cancer sample image, the image of the object under detected is classifying to an esophageal cancer image or a non-esophageal cancer image. Thus, detecting an input image from the image capturing device by the convolutional neural network to judge if the input image is the esophageal cancer image for helping the doctor to interpret the image of the object under detected.

A method, apparatus, electronic device, and storage medium for character recognition are provided. The method may perform image processing on an acquired original image to obtain a region to be recognized. The region may include a character. The method may determine an area ratio of the region to be recognized on the original image. The method may determine an angle between the region to be recognized and a preset direction. The method may determine a character density of the region to be recognized. The method may perform character recognition on the character in the region to be recognized in response to determining that the area ratio is greater than a ratio threshold, the angle is less than an angle threshold, and the character density is less than a density threshold.

Systems, methods and computer program products for detecting objects using a multi-detector are disclosed, according to various embodiments. In one aspect, a computer-implemented method includes defining an analysis profile comprising an initial number of analysis cycles dedicated to each of a plurality of detectors, where each detector is independently configured to detect objects according to a unique set of analysis parameters and/or a unique detector algorithm. The method also includes: receiving digital video data that depicts at least one object; analyzing the digital video data using some or all of the detectors in accordance with the analysis profile, where the analyzing produces an analysis result for each detector used in the analysis. Further, the method includes updating the analysis profile by adjusting the number of analysis cycles dedicated to at least one of the detectors based on the analysis results.

Methods, apparatus, systems, and articles of manufacture are disclosed that decode purchase data using an image. An example apparatus includes processor circuitry to execute machine readable instructions to at least crop an image of a receipt based on detected regions of interest, apply a first mask to a first cropped image to generate first bounding boxes corresponding to rows of the receipt, apply a second mask to a second cropped image to generate second bounding boxes corresponding to columns of the receipt, generate a structure of the receipt by mapping words detected by an optical character recognition engine to corresponding first bounding boxes and second bounding boxes based on a mapping criterion, classify the second bounding boxes by identifying an expression of interest in ones of the second bounding boxes, and generate purchase information by extracting text of interest from the structured receipt based on the classifications.