Abstract: The present disclosure relates to techniques for segmenting objects within medical images using a deep learning network that is localized with object detection based on a derived contrast mechanism. Particularly, aspects are directed to localizing an object of interest within a first medical image having a first characteristic, projecting a bounding box or segmentation mask of the object of interest onto a second medical image having a second characteristic to define a portion of the second medical image, and inputting the portion of the second medical image into a deep learning model that is constructed as a detector using a weighted loss function capable of segmenting the portion of the second medical image and generating a segmentation boundary around the object of interest. The segmentation boundary may be used to calculate a volume of the object of interest for determining a diagnosis and/or a prognosis of a subject.

Abstract: A computer-implemented method for handwritten text line wrapping includes: obtaining, from a user, at least two words of handwritten text on a screen; determining an original bounding box for the at least two words; creating at least one line-break character for the at least two words; determining at least one baseline for the at least two words; determining a new bounding box for the at least two words based on the at least one baseline; generating, on the screen, a text box; moving, on the screen, at least one of the at least two words from a first line of at least one line of handwritten text to a second line of the at least one line of handwritten text, wherein the second line of handwritten text fits within the text box; and adjusting at least one gap between the at least one line of handwritten text.

Abstract: A description support device for displaying information on a topic to be checked in an utterance by a user, the description support device includes: an inputter to acquire input information indicating an utterance sentence corresponding to the utterance; a controller to generate information indicating a check result of the topic for the utterance sentence; and a display to display information generated by the controller, wherein the display is configured to display a checklist indicating whether or not the topic is described in the utterance sentence indicated by the input information sequentially acquired by the inputter, and wherein the display is configured to display, according to a likelihood of each utterance sentence, display information including the utterance sentence, the likelihood defining the check result of the topic in the checklist.

Abstract: Based upon the principles of randomness and self-modification a novel computing machine is constructed. This computing machine executes computations, so that it is difficult to apprehend by an adversary and hijack with malware. These methods can also be used to help thwart reverse engineering of proprietary algorithms, hardware design and other areas of intellectual property. Using quantum randomness in the random instructions and self-modification in the meta instructions, creates computations that are incomputable by a digital computer. In an embodiment, a more powerful computational procedure is created than a computational procedure equivalent to a digital computer procedure. Current digital computer algorithms and procedures can be constructed or designed with ex-machine programs, that are specified by standard instructions, random instructions and meta instructions. A novel computer is invented so that a program's execution is difficult to apprehend.

Abstract: Systems and methods for automated indexing and extraction of information in digital documents are disclosed. A method may comprise identifying a page containing targeted information; inputting an image of the page into a visual machine learning network (visual ML), wherein the visual ML is trained to recognize text associated with the targeted information in an image; identifying by the visual ML, a section of the image that contains the targeted information; inputting the digital document, and coordinates of the section into an extraction module; and extracting the targeted information by the extraction module from the section.

Abstract: The invention provides an image segmentation method and an electronic device. The image segmentation method includes the following steps. Regression analysis is performed on a first gray-scale image to obtain a residual image having an object backbone area. A pixel value of each pixel in the object backbone area is defined as an average gray-scale value of the object backbone area in the residual image, and a second gray-scale image having the object backbone area is generated. It is recursively determined whether a residual polarity of each adjacent pixel adjacent to edge pixels of the object backbone area in the residual image is the same as a residual polarity of the corresponding edge pixel, and whether a pixel value of each adjacent pixel is greater than a first threshold, so as to expand the object backbone area in the second gray-scale image, which is extracted as a target object.

Abstract: Examples provide a self-supervised language model for document-to-document similarity scoring and ranking long documents of arbitrary length in an absence of similarity labels. In a first stage of a two-staged hierarchical scoring, a sentence similarity matrix is created for each paragraph in the candidate document. A sentence similarity score is calculated based on the sentence similarity matrix. In the second stage, a paragraph similarity matrix is constructed based on aggregated sentence similarity scores associated with the first candidate document. A total similarity score for the document is calculated based on the normalize the paragraph similarity matrix for each candidate document in a collection of documents. The model is trained using a masked language model and intra-and-inter document sampling. The documents are ranked based on the similarity scores for the documents.

Abstract: The present disclosure discloses a method and apparatus for recognizing a text. The method comprises: acquiring images of a text area of an input image, the acquired images including a text centerline graph, a text direction offset graph, a text boundary offset graph, and a text character classification graph; extracting coordinates of feature points of a character center from the text centerline graph; sorting the extracted coordinates of the feature points based on the text direction offset graph to obtain a coordinate sequence of the feature points; determining a polygonal bounding box of the text area based on the coordinate sequence of the feature points of the character center and the text boundary offset graph; and determining a classification result of the feature points of the character center, based on the coordinate sequence of the feature points of the character center and the text character classification graph.

Abstract: An electronic voting system is described that utilizes printed vote records (PVRs) in which a voter's vote selections are recorded in voter readable characters. Optical character recognition (OCR) techniques may then be utilized to scan the PVR to record the voter's selections. The OCR data is then utilized to generate the cast vote record. Thus, the electronic voting system directly interprets the voter selections from the PVR just as the voter sees the data. In this manner “what you see is what you get” printed vote record data is provided for a voter's viewing and that same data is used to generate the cast vote record.

Abstract: A computer-implemented method for obtaining content of a document is provided. The method includes: receiving data in an unknown format obtained by an OCR application from the document, the data comprising a plurality of visual elements; for each of the plurality of visual elements, obtaining a position in the document; determining, from the plurality of visual elements, one or more graphic elements and one or more textual elements; determining a particular graphic element from the one or more graphic elements based on the position of the particular graphic element; determining, from the one or more textual elements, a key that is associated with the particular graphic element; determining, from the one or more textual elements, one or more attributes that are associated with the particular graphic element; generating an association between the key and each of the one or more attributes; and providing a structured representation of the association.

Abstract: Techniques for training an optical character recognition (OCR) model to detect and recognize text in images for robotic process automation (RPA) are disclosed. A text detection model and a text recognition model may be trained separately and then combined to produce the OCR model. Synthetic data and a smaller amount of real, human-labeled data may be used for training to increase the speed and accuracy with which the OCR text detection model and the text recognition model can be trained. After the OCR model has been trained, a workflow may be generated that includes an activity calling the OCR model, and a robot implementing the workflow may be generated and deployed.

Abstract: An electronic voting system is described that utilizes printed vote records (PVRs) in which a voter's vote selections are recorded in voter readable characters. Optical character recognition (OCR) techniques may then be utilized to scan the PVR to record the voter's selections. The OCR data is then utilized to generate the cast vote record. Thus, the electronic voting system directly interprets the voter selections from the PVR just as the voter sees the data. In this manner “what you see is what you get” printed vote record data is provided for a voter's viewing and that same data is used to generate the cast vote record.

Abstract: Methods, systems, and computer program products for a customer relationship management (CRM) system are provided herein. Embodiments presented herein provide for exchange of data between disparate, distributed systems; subscribe to and/or publish customer data change event; creation of master records for consumers using static and streaming sources; providing data provenance, auditing capabilities, and queries across multiple tenants and third party systems. Embodiments provide a single view of a customer in a distributed system environment.

Abstract: A method for modifying a printable file includes receiving the printable file; identifying an element representing one or more text characters in the printable file; tagging the element; and incorporating metadata in the printable file, wherein the metadata is associated in the printable file with the tagged element and includes the one or more text characters. A method for using a printable file including at least one tagged graphics object that represents one or more characters and associated metadata includes receiving the printable file; and performing an activity using the printable file and the metadata within the printable file.

Abstract: The present disclosure discloses methods and systems for generating multiple scanned files when scanning a document. The method includes receiving a document for scanning from a user. Once received, a user interface is displayed to the user to input one or more keywords based on which multiple scanned files are to be generated. A single scanned file is generated in a pre-defined format. One or more pages having the keywords as input by the user are identified from the scanned file. Based on the one or more identified pages having the keywords input by the user, separate multiple scanned files are automatically generated. As a result, a single scan activity performed by the user generates multiple scanned files.

Abstract: An information processing apparatus accepts text data. When specifying a word included in the accepted text data, the information processing apparatus generates a code associated with the specified word and generates information that associates the appearance position of the specified word in the text data with the word. The information processing apparatus stores therein the generated code and the information in association with the accepted text data.

Abstract: A document retrieval apparatus includes a processor which receives an input of a keyword, acquires an author's name and a document file from a digital document database which stores document files of text data obtained by performing a character recognition process with respect to document image data of handwritten documents, and names of authors who wrote the handwritten documents, references an associating keyword database which stores information associating the authors' names, keywords, and associating keywords, to acquire an associating keyword of the input keyword, from the received input keyword and the acquired author's name, searches the acquired document file, using the input keyword and the acquired associating keyword, and outputs a search result of the searching.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for receipt decoding. An example apparatus includes processor circuitry to execute instructions to extract text from the receipt image, the text including bounding boxes; associate ones of the bounding boxes to link horizontally related fields of a the receipt image by selecting a first bounding box; identifying first horizontally aligned bounding boxes, the first horizontally aligned bounding boxes to include at least one bounding box of the bounding boxes that is horizontally aligned relative to the first bounding box; adding the first horizontally aligned bounding boxes to a word sync list; and connecting ones of the first horizontally aligned bounding boxes and the first bounding box based on at least one of an amount of the first horizontally aligned bounding boxes in the word sync list and a relationship among the first horizontally aligned bounding boxes and the first bounding box.

Abstract: Described herein are various technologies pertaining to text extraction from a document. A computing device receives the document. The document comprises computer-readable text and a layout, wherein the layout defines positions of the computer-readable text within a two-dimensional area represented by the document. Responsive to receiving the document, the computing device identifies at least one textual element in the computer-readable text based upon spatial factors between portions of the computer-readable text and contextual relationships between the portions of the computer-readable text. The computing device then outputs the at least one textual element.

Abstract: Various implementations disclosed herein include devices, systems, and methods that provide measurements of objects based on a location of a surface of the objects. An exemplary process may include obtaining a three-dimensional (3D) representation of a physical environment that was generated based on depth data and light intensity image data, generating a 3D bounding box corresponding to an object in the physical environment based on the 3D representation, determining a class of the object based on the 3D semantic data, determining a location of a surface of the object based on the class of the object, the location determined by identifying a plane within the 3D bounding box having semantics in the 3D semantic data satisfying surface criteria for the object, and providing a measurement of the object, the measurement of the object determined based on the location of the surface of the object.

Abstract: A document search device includes a document search unit configured to search for an input keyword in a document database in which document information including text data is stored, the text data being extracted, by using a character recognition process, from document image data generated by imaging a paper document, a similar keyword selecting unit configured to select a similar keyword in accordance with a degree of similarity to the input keyword, from a group of wildcard strings generated from the input keyword, and cause the document search unit to search for the similar keyword in the document database, and an output unit configured to output a search result obtained by searching for the input keyword in the document database and a search result obtained by searching for the similar keyword in the document database.

Abstract: Embodiments of the present disclosure provide a method and apparatus for aligning a paragraph and a video. The method may include: acquiring a commentary and a candidate material resource set corresponding to the commentary, a candidate material resource being a video or an image; acquiring a matching degree between each paragraph in the commentary and each candidate material resource in the candidate material resource set; and determining a candidate material resource sequence corresponding to the each paragraph in the commentary based on the matching degrees between the paragraphs in the commentary and the candidate material resources, playing durations of the candidate material resources and text lengths of the paragraphs in the commentary, an image playing duration being a preset image playing duration.

Abstract: A document processing system is configured to identify, for each accessed electronic document in a first set of multiple electronic documents, a set of identified multi-word phrases determined to be in ordered text information in the accessed electronic document, each multi-word phrase of the set of identified multi-word phrases including adjacent words in the ordered text information; and determine, for each accessed electronic document in the first set of multiple electronic documents, a selected document type from the first set of document types based at least on an analysis of the set of identified multi-word phrases with respect to multi-word-phrase characteristics identified by a first definition and associated with each document type in a first set of document types associated with a first document-set type.

Abstract: In one aspect, the present disclosure relates to a method of generating business descriptions performed by a server, said method may include: receiving a plurality of invoices, each invoice being associated with a business of a plurality of businesses; extracting a plurality of texts from the plurality of invoices; embedding the plurality of texts to a vector space to obtain a plurality of invoice vectors; generating a plurality of clusters in the vector space, each cluster of the plurality of clusters comprising at least one invoice vector of the plurality of invoice vectors; generating a description for a cluster, the description for the cluster representing all invoice vectors assigned to the cluster; for each business of the plurality of businesses that has at least one invoice vector assigned to the cluster, associating the business with the description; and indexing the plurality of businesses within a database by the generated descriptions.

Abstract: In an approach for providing a document access control based on document component layouts, a processor detects a layout of a document, the layout including one or more components of the document. A processor defines an access policy to access the one or more components based on the layout. A processor authorizes a request to access the one or more components based on the access policy and the layout. A processor retrieves the one or more components based on the access policy and the authorized request.

Abstract: A system performs optical character recognition (OCR) on an image displaying a portion of an object. An image classification system identifies the object in the image, based on which one or more object detection models identify labels associated with the object within the image. The system determines text of the identified labels using OCR, and analyzes the OCR resultant text for discrepancies and/or inaccuracies. In response to identifying a discrepancy, the system provides a recommendation for improving the accuracy of the OCR resultant text.

Abstract: Systems and methods for automated indexing and extraction of information in digital documents are disclosed. A method may comprise selecting a page number of a digital document to identify a page containing targeted information; inputting an image of the page into a visual machine learning network (visual ML), wherein the visual ML is trained to recognize text associated with the targeted information in an image; identifying by the visual ML, a section of the image that contains the targeted information; inputting the page number, the digital document, and coordinates of the section into an extraction module; and extracting the targeted information by the extraction module from the section.

Abstract: Disclosed herein are system, method, and computer program product embodiments for maintaining of a geometric object in a database. An embodiment operates by a database maintaining a first page storing a data block in the database's on-disk store such that the data block stores at least one byte of the geometric object. After receiving the request for the geometric object, the database loads the page storing the geometric object in the in-memory store and determines the size of the geometric object. Based on the size of the geometric object, the database stores the geometric object in the in-memory store directly or in a heap of the in-memory store.

Abstract: A language determination model may be applied to select a first machine learning model or a second machine learning model to analyze the input text. The first machine learning model trained to analyze text in a first language, the second machine learning model trained to analyze text in a second language, and the input text may be in a third language. The language determination model may select the first machine learning model based on the first machine learning model having a better performance analyzing text in the third language than the second machine learning model. The language determination model may be updated based on an actual performance of the first machine learning model analyzing the input text. Moreover, the first machine learning model may be subject to additional training if the actual performance of the first machine learning model analyzing the input text is below a threshold value.

Abstract: Various methods, apparatuses/systems, and media for automatically extracting information from unstructured data are provided. A receiver receives digitized data of a document having unstructured data format. A processor applies machine learning models for sectioning the digitized data. An OCR device applies an OCR processing to the sectioned digitized data. The processor matches the sectioned digitized data to patterns and rules; applies classification models to the matched digitized data to identify entities and events from the sectioned digitized data; automatically link each entity with corresponding event in a hierarchical format to generate a document having structured data format; and output the document having the structured data with metadata having the linked entity with corresponding event in the hierarchical format to downstream applications.

Abstract: Systems and methods for executing a robotic process automation (RPA) workflow are provided. The RPA workflow is executed by a first robot. The execution of the RPA workflow is suspended by the first robot. A current context of the RPA workflow is serialized at a time of the suspension and the current context of the RPA workflow is stored. The execution of the RPA workflow is resumed by a second robot based on a triggering condition by retrieving the current context of the RPA workflow. The first robot and the second robot may be the same robot or different robots.

Abstract: An automated content annotation workflow is disclosed. An example embodiment is configured for: registering a plurality of labelers to which annotation tasks are assigned; populating a labeling queue with content data to be annotated; assigning annotation tasks from the labeling queue to the plurality of labelers; enabling the plurality of labelers in an annotation review queue to modify or delete annotations applied by prior labelers; and evaluating a level of performance of the plurality of labelers in applying the annotations.

Abstract: 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.

Abstract: Disclosed is an approach of on-device partial recognition that includes performing partial recognition on an image of a document captured by a mobile device to detect and/or recognize a specific area (e.g., barcodes, non-relevant text, etc.) and filling the recognized area with a solid color. Because the solid color area has a maximum compression ratio, this approach can lead to image size reduction and increased network throughput for client-server based data recognition where further processing such as advanced data extraction is performed at the server side. The approach can be enforced with neural network algorithms to exclude non-relevant information (e.g., logos, phrases, words, etc.).

Abstract: Systems and methods for text segmentation are described. Embodiments of the inventive concept are configured to receive an image including a foreground text portion and a background portion, classify each pixel of the image as foreground text or background using a neural network that refines a segmentation prediction using a key vector representing features of the foreground text portion, wherein the key vector is based on the segmentation prediction, and identify the foreground text portion based on the classification.

Abstract: The present disclosure relates to UI systems and processes including methods for controlling text position in a computer display. A target word in a body of text may be maintained in position by forward rendering and backward rendering, iteratively as the text is modified by the addition or deletion of words or by modifications affecting height or width of a word.

Abstract: Systems and methods include obtaining a set of events, each event in the set of events comprising a time-stamped portion of raw machine data, the raw machine data produced by one or more components within an information technology or security environment and reflects activity within the information technology or security environment. Thereafter, a first neural network is used to automatically identify variable text to extract as a field from the set of events. An indication of the variable text is provided as a field extraction recommendation, for example, to a user device for presentation to a user.

Abstract: An image processing apparatus according to the present disclosure is an image processing apparatus for automatically transmitting a document file by using a result of a character recognition process on a scan image of a document as a property, and includes: at least one processor that executes the program to perform: extracting a confidence factor indicating a degree of certainty of the result of the character recognition process; in a case where the extracted confidence factor is above a predetermined threshold value, determining that the document file using the result of the character recognition process as the property is allowed to be automatically transmitted; and setting the predetermined threshold value such that an incorrect transmission ratio of document files to be automatically transmitted reaches a target incorrect transmission ratio.

Abstract: A document retrieval apparatus includes: a storage unit that stores documents and dictionaries applied to a model, a correspondence between a model and documents applied to the model, and a correspondence between a document and dictionaries applied to the dictionary; a model selecting unit that selects a model; a search target document specifying unit that specifies documents applied to the model selected by the model selecting unit as search target documents; a dictionary specifying unit that specifies dictionaries applied to the search target document; a query receiving unit that inputs a query; a search keyword extraction unit that extracts a search keyword group by applying the dictionary specified by the dictionary specifying unit to the query; a retrieving unit that retrieves the search target document using the search keyword group; and a retrieval result presenting unit that displays search results retrieved by the retrieving unit.

Abstract: An electronic device according to various embodiments includes a communication circuit, a memory, and a processor, and the processor is configured to: receive a first image from a first external electronic device by using the communication circuit; perform image recognition with respect to the first image by using the first image; generate information regarding an external object included in the first image, based on a result of the recognition; based on the information regarding the external object satisfying a first designated condition, transmit at least a portion of the first image to a second external electronic device corresponding to the first designated condition; and, based on the information regarding the external object satisfying a second designated condition, transmit the at least portion of the first image to a third external electronic device corresponding to the second designated condition.

Abstract: An automated documentation intake and processing system involves pre-processing source images of intake documents and applying a YOLO CNN model to identify fields of interest (FOIs) therein which may contain target data. The system classifies FOIs and upsamples the contents in order to digitize and extract target data. The system may be trained to differentiate between target data and non-target data and incorporates an adjustable confidence scores which reflects the system's degree of accuracy at predicting the correct FOI (e.g., name, address, insurance number, vehicle registration number). The system is pre-trained to detect a subset of documentation types, form fields, and form field types. However, the system is configured to adapt to variations of the same types of documentation, such as different insurance cards or driver licenses from different states.

Abstract: Detection of typed and/or pasted text, caret tracking, and active element detection for a computing system are disclosed. The location on the screen associated with a computing system where the user has been typing or pasting text, potentially including hot keys or other keys that do not cause visible characters to appear, can be identified and the physical position on the screen where typing or pasting occurred can be provided based on the current resolution of where one or more characters appeared, where the cursor was blinking, or both. This can be done by identifying locations on the screen where changes occurred and performing text recognition and/or caret detection on these locations. The physical position of the typing or pasting activity allows determination of an active or focused element in an application displayed on the screen.

Abstract: An inference method includes acquiring similarities between a domain name serving as an analysis object and each domain name indicated in a legitimate domain name list as feature amounts, and inferring a degree that the domain name serving as the analysis object is wrongly recognized as a legitimate domain name based on the feature amounts acquired at the acquiring and a training model that outputs, as a response to input of the feature amounts, a degree that the domain name serving as the analysis object is wrongly recognized as the legitimate domain name, by processing circuitry.

Abstract: Various aspects of the present disclosure generally relate to optical character detection. In some aspects, a user device may receive, from a vision sensor, a first image that is associated with a first optical character image. The user device may determine, using an image processing model, that the first image depicts the first optical character image. The user device may cause, based at least in part on determining that the first image depicts the first optical character image, a camera to capture a second image that is associated with a second optical character image. The user device may perform an action associated with the second image. Numerous other aspects are provided.

Abstract: An image processing method, an image processing device, an electronic device, and a non-transitory computer readable storage medium are provided.

Abstract: In an approach, a processor groups documents into a plurality of groups based on similarity, where: documents of each group have a same document structure; and the document structure is defined by coordinates of text blocks. A processor, for each group of the plurality of groups and for each document of the respective group: retrieves a value of each text block of the respective document in accordance with a document structure of the group; and assigns to each text block of the respective document an attribute that represents the retrieved value of the text block. A processor assigns a first document of the documents to an entity of a database that matches the first document based on the group of text block values and the assigned attributes of the document.

Abstract: An electronic device according to various embodiments includes a communication circuit, a memory, and a processor, and the processor is configured to: receive a first image from a first external electronic device by using the communication circuit; perform image recognition with respect to the first image by using the first image; generate information regarding an external object included in the first image, based on a result of the recognition; based on the information regarding the external object satisfying a first designated condition, transmit at least a portion of the first image to a second external electronic device corresponding to the first designated condition; and, based on the information regarding the external object satisfying a second designated condition, transmit the at least portion of the first image to a third external electronic device corresponding to the second designated condition.

Abstract: Disclosed is an effective domain name defense solution in which a domain name string may be provided to or obtained by a computer embodying a visual domain analyzer. The domain name string may be rendered or otherwise converted to an image. An optical character recognition function may be applied to the image to read out a text string which can then be compared with a protected domain name to determine whether the text string generated by the optical character recognition function from the image converted from the domain name string is similar to or matches the protected domain name. This visual domain analysis can be dynamically applied in an online process or proactively applied in an offline process to hundreds of millions of domain names.

Abstract: Disclosed are various embodiments for integrating an email client with hosted applications. An email is received from an email client. An image that is a component of the email is identified and sent to an optical character recognition (OCR) service. Extracted text is received from the OCR service. A request for an action object is then sent to a connector for an application, the action object representing a potential action that could be performed with the application based on the extracted text from the OCR service. The action object is then sent to the email client, which is configured to display a prompt allowing a user to perform the action represented by the action object.

Abstract: Herein are quantitative analytics to increase the accuracy of cardinality estimation without increasing sample size. In an embodiment, a computer selects a few sample values from a multiset. A high-frequency exact count of distinct values that have at least a threshold amount of occurrences in the sample values is counted. A low-frequency exact count of distinct values in the sample that do not have at least the threshold amount of occurrences in the sample is counted. Based on multiple binomial probabilities, an upper bound of a count of missing distinct values in the multiset that are not in the sample is calculated. A total count of distinct values (NDV) in the multiset is estimated based on: a) the high-frequency exact count of distinct values, b) the low-frequency exact count of distinct values, and c) the upper bound of the count of missing distinct values in the multiset that are not in the sample.