The system may include a method comprising requesting, by a computer, a receiver identifier associated with a receiver; receiving, by the computer, the receiver identifier in association with content; constructing, by the computer, a URL link comprising access to DICOM viewer code, DICOM data for the selected images, a sender identifier and the receiver identifier; generating, by the computer, a notification to the receiver, wherein the notification includes the URL link; and transmitting, by the computer, the notification to a receiver based on the receiver identifier.

Systems, methods, and other techniques for extracting data from obituaries are provided. In some embodiments, an obituary containing a plurality of words is received. Using a machine learning model, an entity tag from a set of entity tags may be assigned to each of one or more words of the plurality of words. Each particular tag from the set of entity tags may include a relationship component and a category component. The relationship component may indicate a relationship between a particular word and the deceased individual. The category component may indicate a categorization of the particular word to a particular category from a set of categories. The extracted data may be stored in a genealogical database.

A method for processing a system image, which represents an image of a file system. Each file in the file system is assigned an attribute, this attribute representing a last access time to this file, Initially the attributes of all files are set to a predefined value. The system image is executed, and then all attributes being checked. Finally the files are deleted whose attribute has the preset value.

Disclosed herein are systems and method for classifying objects in an image using a color-based machine learning classifier. A method may include: training, with a dataset including a plurality of images, a machine learning classifier to classify an object in a given image into a color class from a set of color classes of a first size; receiving an input image depicting at least one object belonging to the set of color classes; determining a subset of color classes that are anticipated to be in the input image based on metadata of the input image; generating a matched mask input indicating the subset set of color classes in the input image, wherein the subset of color classes is of a second size that is smaller than the first size; and inputting both the input image and the matched mask input into the machine learning classifier.

Example embodiments may provide a system, apparatus, computer readable media, and/or method configured for processing input representing data associated with a first product, the first product comprising a plurality of components, processing input representing a particular one of the components, processing input representing an attribute of the particular component or of the first product, querying a product memory based on the particular component and the attribute to identify a second product.

Example embodiments may provide a system, apparatus, computer readable media, and/or method configured for processing input representing data associated with a first product, the first product comprising a plurality of components, processing input representing a particular one of the components, processing input representing an attribute of the particular component or of the first product, querying a product memory based on the particular component and the attribute to identify a second product.

A system for updating a database comprises an input interface and a processor. The input interface is configured to receive image data. The processor is configured to determine from the image data one or more attributes of a database entry for real estate property and update the database entry for the real estate property.

In one aspect, an example method to be performed by a computing device includes (a) receiving a request to use a camera of the computing device; (b) in response to receiving the request, (i) using a microphone of the computing device to capture audio content and (ii) using the camera of the computing device to capture an image; (c) identifying reference audio content that has at least a threshold extent of similarity with the captured audio content; and (d) outputting an indication of the identified reference audio content while displaying the captured image.

The present invention provides a presenting device and analytics device. The presenting device comprises a storage means comprising first data and second data, wherein the first data is of a higher security classification than the second data; a controller configured to generate a first computer-readable tag based on the second data; and image generation means configured to generate an image for display on a display apparatus, the image comprising the first data and the first computer-readable tag. The analytics device comprises a reader for reading the computer-readable tag and a controller for decoding the computer-readable tag and identifying data associated therewith. The present invention also provides a system comprising the presenting device and an analytics device and a methods of presenting and analysing data.

A work machine including a sensing device, a user interface, and a control unit is disclosed. The control unit may be configured to generate a productivity layer based on productivity data, and generate an image layer based on image data. The image data may include information relating to an image corresponding to a state of an operation associated with a worksite and a geospatial reference associated with the image. The control unit may be configured to generate a composite image of the worksite based on a map layer, the image layer, and the productivity layer, and cause the composite image to be displayed via the user interface. The composite image may position the image layer relative to the map layer based on the geospatial reference and geographical coordinates corresponding to the geospatial reference, and position the productivity layer relative to the image layer.