The present disclosure is related to visual annotations on medical images. A system may include a processor configured to process input data and identify a relationship amongst received input data in a data set. The system may also include an aggregator coupled to the processor and configured to receive processed data from the processor and aggregate data within the data set while maintaining one or more data relationships within the data set. Further, the system may include an annotation service module coupled to the aggregator and configured to generate at least one annotation that is maintained across at least a portion of the data within the data set.

A system includes a microscope configured to magnify a pathology sample, a camera positioned to record magnified pathology images from the microscope, and a display configured to show the magnified pathology images. A processing apparatus is coupled to the camera, and the display, and the processing apparatus includes instructions that when executed by the processing apparatus cause the system to perform operations, including: identifying, using a machine learning algorithm, one or more regions of interest in the magnified pathology images; and alerting, using the display, a user of the microscope to the one or more regions of interest in the magnified pathology images while the pathology sample is being magnified with the microscope.

A system includes a microscope configured to magnify a pathology sample, a camera positioned to record magnified pathology images from the microscope, and a display configured to show the magnified pathology images. A processing apparatus is coupled to the camera, and the display, and the processing apparatus includes instructions that when executed by the processing apparatus cause the system to perform operations, including: identifying, using a machine learning algorithm, one or more regions of interest in the magnified pathology images; and alerting, using the display, a user of the microscope to the one or more regions of interest in the magnified pathology images while the pathology sample is being magnified with the microscope.

Electronic devices are disclosed. A first device stores items, parent categories, images, child categories and product information for each item. The first device receives a search image from a second device, determines a parent category and a child category of the search item, identifies a first database from among the databases matching the determined parent category of the search item, when the child category is determined, identifies a subset of the stored items corresponding the first database that match the search image based on at least one feature of the received search image and the determined child category of the received search image, and transmits information on the identified subset of the stored items to the external electronic device. The second device transmits the image of a first item to the first device, and receives a transmission indicating one or more second items matching the transmitted image for display.

The present disclosure provides an image acquisition method, image acquisition device, electronic device, and computer-readable storage medium. The method includes: acquiring an image retrieval text input by a user and a screen display status of an image display device; determining retrieval intention information and a retrieval keyword according to the image retrieval text, wherein the retrieval intention information comprises information reflecting the user's retrieval intention, and the retrieval keyword comprises a keyword used to retrieve images; acquiring at least one candidate image according to the retrieval intention information and the retrieval keyword; and selecting a target image from the at least one candidate image according to the screen display status.

The present disclosure provides an image acquisition method, image acquisition device, electronic device, and computer-readable storage medium. The method includes: acquiring an image retrieval text input by a user and a screen display status of an image display device; determining retrieval intention information and a retrieval keyword according to the image retrieval text, wherein the retrieval intention information comprises information reflecting the user's retrieval intention, and the retrieval keyword comprises a keyword used to retrieve images; acquiring at least one candidate image according to the retrieval intention information and the retrieval keyword; and selecting a target image from the at least one candidate image according to the screen display status.

Technologies generally described herein relate to a computing device for an input assistance scheme for an online marketplace posting. In one aspect, a computing device receives an input image containing an object to be posted on an online marketplace. In response to receiving the object, the computing device extracts, from the input image, feature data relating to the object. The device performs a search of an image database based on the extracted feature data to determine one or more images containing the object. The computing device obtains information data of the determined images and generates a reference dataset for the object based on the reference dataset.

Disclosed herein are methods and systems of metadata management for reviewing data from microscopy experimental sessions. Image data from an experimental session is stored in an archive at one or more filepath locations, either locally or on a network. Metadata associated with the image data is stored in a database with a reference to the filepath where the raw image is stored, such that the metadata is associated in the database with the image data. A user can perform post-experimental filtering, sorting, and searching of the underlying image data using the metadata, which allows the image data to be analyzed without duplication of the image data and without manual review of each individual image. The filtered data is presented in an interactive timeline format.

A method for providing data associated with a shopping mall web page includes accessing a review item written by a user ID in association with the shopping mall web page, the review item including an image and a text; detecting at least one target object from the image included in the review item; processing the detected target object to generate first feature data; processing a reference object included in the shopping mall web page to generate second feature data corresponding to the reference object; and outputting verification data indicating a result of verification for the review item by comparing the first feature data, generated by processing the target object, with the second feature data, generated by processing the reference object.

Disclosed is a secure telephone call management system for authenticating users of a telephone system in an institutional facility. Authentication of the users is accomplished by using a personal identification number, preferably in conjunction with speaker independent voice recognition and speaker dependent voice identification. When a user first enters the system, the user speaks his or her name which is used as a sample voice print. During each subsequent use of the system, the user is required to speak his or her name. Voice identification software is used to verify that the provided speech matches the sample voice print. The secure system includes accounting software to limit access based on funds in a user's account or other related limitations. Management software implements widespread or local changes to the system and can modify or set any number of user account parameters.