An image processing device with intelligent typesetting function and method thereof is provided. A processor is connected to an image capture module, a memory module and an output module respectively. A first image is acquired by the image capture module and a set of scanning position information in the memory module. A set of typesetting parameters is applied to the corresponding scanning position information. The processor continues to obtain a second side image through the image capture module and applies the set of typesetting parameters. The processor generates a typesetting image based on the set of typesetting parameters, the first side image and the second side image, and causes the output module to output the typesetting image. Through intuitive scanning procedures and intelligent and quick application of preset image typesetting methods, tedious operations are reduced, thereby improving efficiency and convenience.

An information processing device on a server side includes: a predetermined number of recognition units, for which a model updated by performing image recognition in a predetermined number of vehicles and executing unsupervised learning is each set, configured to perform image recognition on an image, on which image recognition has been performed in a predetermined number of the vehicles; and an evaluation value calculation unit configured to evaluate recognition results obtained in a predetermined number of the recognition units and calculate an evaluation value for each of the recognition units. The information processing device on the vehicle side includes an execution unit that executes unsupervised learning, and a determination unit that determines whether learning has been performed correctly or not for a model updated in the execution unit on the basis of an evaluation value found on the server side.

A method of generating an image sample, which relates to a field of an artificial intelligence technology, in particular to fields of a deep learning technology and a computer vision technology. The method includes: generating a handwritten text image according to at least one handwritten sample image; and generating a target sample image with an annotation box according to the handwritten text image and a background image, where the annotation box is used to represent a region in which the handwritten text image is located in the background image. The present disclosure further provides a method of recognizing a text, an electronic device and a storage medium.

Disclosed is an operating system (OS) discovery mode that identifies and provides access to OS and/or third-party provided features within an applicable region of a desktop. In some configurations, once the discovery mode is activated, the content displayed by the applicable region is analyzed to identify content usable by OS and/or third-party provided features. Visual cues are rendered in the applicable region near the identified content, highlighting the availability of the OS and/or third-party provided features. Users may interact with the visual cues to manipulate the underlying content or to invoke the OS and/or third-party provided features. OS and/or third-party provided features may modify content displayed by an application, launch an inline micro-experience, crop or export images, etc. While in the discovery mode, visual cues are highlighted as a discovery mouse cursor moves around the desktop. In some configurations the discovery mode is triggered automatically, causing an OS service to automatically identify and display a set of entity visual cues across the applicable region.

An interactive system for identifying and correcting inconsistencies between a written work, an audio reading of the written work, and a resulting transcription of the audio reading. The system stores on a computing device connected to a network a manuscript, an audio version of the manuscript, and a transcription of the audio version of the manuscript. Via a transcription engine, difference and comparison engine, and a user device having a visual interface, a user is visually presented via the display the inconsistencies between the transcript and the manuscript, the user can amend the manuscript and/or the transcript to reconcile the works, the user can listen to a corresponding section of the corresponding audio file, and the user can interact with collaborators in a context aware interface. Upon the user processing, the manuscript may be read and listened to simultaneously as an enhanced e-book through a separate software tool.

A drawing search server specifies an arrangement of plural boxes existing in a title field title field existing in target drawing data. The drawing search server executes character recognition processing on each character string existing at each position in the title field existing in the target drawing data. Based on the character recognition result and the arrangement of the plural boxes, the drawing search server specifies a target attribute value representing an attribute value of the target drawing data and specifies a target attribute which is an attribute associated in advance with the box. The drawing search server searches a drawing database for drawing data having an attribute value similar to the attribute value of the target drawing data based on a combination of the target attribute value and the target attribute, and outputs a search result.

A table-image recognition device includes: an object extracting unit that extracts a plurality of objects included in a table; a set determination unit that determines whether or not every pair consisting of two objects selected from the plurality of objects is a set constituting a component specified by a column and a row of the table; a same-row determination unit that determines whether or not the objects of each pair share a same row; a same-column determination unit that determines whether or not the two objects of each pair share a same column; and a structure determining unit that determines a structure of the table by specifying the row and column to which each object belongs on the basis of the determination result.

A method for collecting machine data from a machine comprising the following steps: collecting image information displayed on a graphical user interface of a machine and transmitting the collected information to a computer unit; masking the collected information or information derived therefrom to define data regions; extracting alphanumeric characters from at least one data region by means of a text recognition program; writing the alphanumeric characters into a data structure; and storing or outputting the data structure.

Optical character recognition (OCR) based systems and methods for extracting and automatically evaluating contextual and identification information and associated metadata from an image utilizing enhanced image processing techniques and image segmentation. A unique, comprehensive integration with an account provider system and other third party systems may be utilized to automate the execution of an action associated with an online account. The system may evaluate text extracted from a captured image utilizing machine learning processing to classify an image type for the captured image, and select an optical character recognition model based on the classified image type. They system may compare a data value extracted from the recognized text for a particular data type with an associated online account data value for the particular data type to evaluate whether to automatically execute an action associated with the online account linked to the image based on the data value comparison.

Exemplary embodiments of present disclosure are directed towards a system and method for extracting objects from videos in real-time to create virtual situations, comprising a computing device comprises video creating and editing module configured to enable a user to record videos and select frames automatically from the user recorded videos thereby transferring the automatically selected frames from the computing device to a server. The server comprises video processing module configured receive the automatically selected frames thereby detecting and extracting objects from the automatically selected frames and transfer extracted objects to computing device and display the extracted objects to the user. The video creating and editing module configured to place the extracted objects on a new frame automatically and allow the user to reposition extracted objects on new frame and enable the user to customize the background and foreground elements in the new frame to create virtual situations.