This disclosure provides a video generation method, a video generation apparatus, an electronic device, a storage medium and a program product, and relates to the field of artificial intelligence technology, and in particular to the field of computer vision technology and deep learning technology. A specific implementation includes: obtaining document content information of a document; extracting, from the document content information, populating information for multiple scenes in a preset video template; populating the populating information for the multiple scenes into corresponding scenes in the preset video template, respectively, to obtain image information of the multiple scenes; generating audio information of the multiple scenes according to the populating information for the multiple scenes; generating a video of the document based on the image information and audio information of the multiple scenes.

An information processing apparatus capable of switching execution of an inspection process depending on a transmission destination. The information processing apparatus includes at least one memory device that stores a set of instructions, and at least one processor that executes the set of instructions to: extract a character string from scan data obtained by scanning a document, control to execute an inspection process, which determines whether a predetermined character string registered beforehand is included in the extracted character string, in a case where a first transmission destination is designated as information about a transmission destination of the scan data, and control not to execute the inspection process in a case where a second transmission destination different from the first transmission destinations is designated as the information about the transmission destination of the scan data.

A processor-implemented method includes (i) defining a region of interest ranging between a first and second boundary location for each label in the M documents that comprise N labels, (ii) summarizing information, in a selected document, from a first content location to the first boundary location of the region of interest to obtain a first summary that represents context information from the first content location to the first boundary location of the region of interest, (iii) summarizing information, in the selected document, from a second content location to the second boundary location to obtain a second summary that represents context information from the second boundary location to the second content location, (iv) performing training of the AI model including restricting training data from the M documents based on the region of interest, and (v) extracting the target data from the M documents using trained AI model.

The present invention relates to a method 300, an interface 40, and computer code for adapting a data structure of an input data set for processing in a computer system 14. The method comprises receiving, in a data processing device 20, the input data set including plurality of data posts, identifying identifiers in the input data set, each identifier being connected to at least one data post received in the input data set and indicating the sort of data represented by the connected data post, displaying a first subset of the data posts 46 from the input data set in a display view 42, wherein each data post 46 is displayed at a specified position within a display area related to the identifier of the data post 46, mapping, in the data processing device 20, the received data set identifiers relating to each of a second subset of the data posts to identifiers of data posts in a capture data set, displaying the second subset of the data posts in a dynamic rearrangement view 44, wherein each data post 50 of the second subset is displayed in a field 50 connected to the identifier related to the data post 50 displayed, receiving a first identifier connected to a data post 46 selected in the display view, receiving a second identifier connected to a data post 50 selected in the rearrangement view, remapping, in the data processing device 20, the data post connected to the first identifier to the data post in the capture data set connected to the second identifier, and sending the remapped capture data set to the computer system 14 for processing based on the connected identifiers.

An apparatus and method for generating a schema, the apparatus comprising at least a processor and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to display, at a graphical control interface, a content field window, receive, as a function of the content field window, a criterion element, and generate a schema as a function of the criterion element.

The present invention provides a document display assistance system which estimates and highlights significant words in a document of a specific field. The system comprises: a database in which selection-target words and non-selection-target words are registered; a learned word-selection model having been applied with machine learning for estimating whether a word is a selection-target word; a text pre-processing unit which segments words from an accepted display-target document; a word classification unit which classifies, based on the database, the word into any of a selection-target word, a non-selection-target word, and an indeterminate word; a text post-processing unit which generates output data by imparting a predetermined attribute to a predetermined word in the display-target document; and an output unit which outputs the output data. If a label is estimated indicating that the indeterminate word classified by the word classification unit is a selection-target word, the word selection model classifies the indeterminate word into a selection-target word and the text post-processing unit imparts the predetermined attribute to the classified selection-target word.

The present disclosure relates to management of synthetic media detection determinations and automatic generation of notifications thereof. Processing of the present disclosure provides a synthetic media detection component, able to be integrated with a plurality of host application/services, where the synthetic media detection component is adapted to work as a trust factor that automatically generates predictive determinations as to whether digital content has been digitally altered. In doing so, trained artificial intelligence processing is applied that executes a contextual analysis of digital content and generates a determination as to whether digital content (or a portion thereof) may be synthetic media. Notifications are automatically generated and provided for rendering across any host application/service endpoints that provide a representation of the digital content including future representations of digital content. Automated generation and transmission of synthetic media detection determinations are aimed at combatting disinformation and subsequent presentation of untrusted/unauthenticated digital content.

The present disclosure discloses methods and systems for automatically detecting Infrared (IR) security mark based on unknown halftone frequency information. The method includes receiving a document from a user including an IR security mark. The document is scanned. Then, one or more halftone frequencies associated with the IR security mark portion are estimated. Based on the estimation, the IR security mark portion is classified into a background region and the IR marked region including the IR security mark. The IR security mark is extracted and pixels falling in the IR marked region are reconstructed to identify content in the IR security mark. Finally, the identified content is compared with one or more pre-stored IR security marks to ascertain the presence of the IR security mark in the document for further assessment. This way, the method automatically detects the IR security mark in the document.

An image outputting device includes a scanning module, a storage module, an identification module, a calibration module and a printing module. The scanning module generates an image by scanning an object. The storage module stores the image. The identification module identifies a layout orientation and a text orientation of the image. The calibration module calibrates the layout orientation and the text orientation of the image according to a relation of an identification result of the identification module and a layout orientation of the printing medium. When the printing module prints the calibrated image on a printing surface of the printing medium and outputs the printing medium with the printing surface facing downwardly, the layout orientation of the printed image matches with the layout orientation of the printing medium, and the text orientation of the printed image is opposite to an medium outputting direction or arranged from proximal to distal.

Provided is a method, computer program product, and system for classifying a set of data items based on format organizations. A processor may determine at least one format organization of a set of data items. The format organization of a data item indicates a symbol type of at least one continuous symbol in the data item and a number of the at least one continuous symbol. The processor may determine at least one candidate data class for the set of data items from a plurality of predetermined data classes based on the at least one format organization. The processor may classify the set of data items into at least one target data class selected from the at least one candidate data class. In this way, the set of data items can be efficiently classified.