Systems and methods are provided for disambiguating entities in a mobile environment and using the disambiguated entity to perform actions. An example method includes identifying an ambiguous entity reference in a screen shot of an interface generated by a first mobile application executing on a mobile device, determining a chronological window of content captured prior to the screen shot, and identifying a plurality of entities appearing in the chronological window of content. The method also includes disambiguating the ambiguous entity reference using the plurality of entities appearing in the chronological window and using the disambiguated entity to perform an action in a second mobile application executing on the mobile device.

The present disclosure relates to apparatus and method for training a learning system to detect event. The present disclosure provides apparatus and method for training a learning system that includes an event related keyword collecting unit that collects an event related keyword inputted by a user, a related keyword collecting unit that collects at least one related keyword from a word database by transmitting an event related keyword to the word database, an event related image collecting unit that collects at least one event related image that is related to a search formula from an image database by transmitting the search formula to the image database, and a training unit that trains a learning system by communicating with the learning system with a use of an event related image as training data. In consequence, it is capable of setting a specific event to be detected by an apparatus for training a learning system by a user after a system is installed, and it is possible to train a learning system sustainably and sufficiently regarding a specific event and achieve a high accuracy of training the learning system.

An image item processing engine for image item exchange may receive an image item data packet including two image items, each including a digital image documenting an action for a recipient institution and associated metadata. The metadata may identify the image item sender and a country associated with an image item, the packet originator, or the recipient institution, at least one country associated with the second image item being different than a country associated with the first image item. The engine may apply sorting rules to determine item types for the first and second image items based on their metadata, determine a recipient institution for the packet based on the item types, assemble a data transfer packet including the digital images and metadata included in the first and second image items, and provide the data transfer packet to a transfer packet routing service for routing to the selected recipient institution.

An image item processing engine for image item exchange may receive an image item data packet including two image items, each including a digital image documenting an action for a recipient institution and associated metadata. The metadata may identify the image item sender and a country associated with an image item, the packet originator, or the recipient institution, at least one country associated with the second image item being different than a country associated with the first image item. The engine may apply sorting rules to determine item types for the first and second image items based on their metadata, determine a recipient institution for the packet based on the item types, assemble a data transfer packet including the digital images and metadata included in the first and second image items, and provide the data transfer packet to a transfer packet routing service for routing to the selected recipient institution.

Embodiments of the present invention disclose a method, computer program product, and system for unlocking emoticons based on professional skills. The computer may receive a user message or an emoticon database search term from a user, wherein a user's professional skill and an associated emoticon is determined based on the user message or the emoticon database search term. A plurality of user professional skills may be retrieved from a professional skills site. It may be determined whether a number of endorsements for the user's professional skill exceeds a threshold value, wherein the threshold value is set for each emoticon in an emoticon database. In response to it being determined that the number of endorsements for the user's professional skill does exceed the threshold value, an unlocking action may be performed that gives the user access to the associated emoticon in one or more messaging applications based on the determination.

Systems and techniques are provided for a data matching system having a plurality of clients and a master catalog. In a learning phase of a client, the data matching system builds a client matching table for the client and matches the input request to a specific entry in a particular set of entries in the master catalog. In a post-learning phase of the client, the data matching system uses the client matching table to match the input request to a specific entry in a particular set of entries in the master catalog. In a specific implementation, the data matching system uses a two-step match to build the client matching table. In a first step, a plurality of a set of entries in the master catalog is selected for the input request. In a second step, a particular set of entries is selected using a confidence score.

A mechanism is provided in a data processing system comprising a processor and a memory, the memory comprising instructions that are executed by the processor to specifically configure the processor to implement a medical imaging story board creation engine. The medical imaging story board creation engine executing in the data processing system receives a patient data structure comprising a medical imaging study comprising a plurality of electronic medical images. The medical imaging story board creation engine analyzes the patient data structure to determine a modality of the medical imaging study. The medical imaging story board creation engine determines, based on the determined modality of the medical imaging study, for each electronic image in the medical imaging study, at least one of an image mode or viewpoint. The medical imaging story board creation engine performs a saliency feature extraction operation on the electronic medical images in the medical imaging study based on the image mode or viewpoint of each of the electronic medical images. The medical imaging story board creation engine selects a subset of electronic medical images based on results of the saliency feature extraction. The medical imaging story board creation engine generates and outputs a collection of selected electronic medical images based on the selection of the subset of electronic medical images to form a medical imaging story board.

In some aspects, the described systems and methods provide for a method for training a statistical model to predict tissue characteristics for a pathology image. The method includes accessing annotated pathology images. Each of the images includes an annotation describing a tissue characteristic category for a portion of the image. A set of training patches and a corresponding set of annotations are defined using an annotated pathology image. Each of the training patches in the set includes values obtained from a respective subset of pixels in the annotated pathology image and is associated with a corresponding patch annotation determined based on an annotation associated with the respective subset of pixels. The statistical model is trained based on the set of training patches and the corresponding set of patch annotations. The trained statistical model is stored on at least one storage device.

Computerized systems and methods are disclosed, including a computer system that executes software that may receive a geographic location having one or more coordinates of a structure, receive a validation of the structure location, and generate unmanned aircraft information based on the one or more coordinates of the validated location. The unmanned aircraft information may include an offset from the walls of the structure to direct an unmanned aircraft to fly an autonomous flight path offset from the walls, and camera control information to direct a camera of the unmanned aircraft to capture images of the walls at a predetermined time interval while the unmanned aircraft is flying the flight path. The computer system may receive images of the walls captured by the camera while the unmanned aircraft is flying the autonomous flight path and generate a structure report based at least in part on the images.

Provided is a method of classifying, into an album, one or more image files stored in a terminal with a screen to which a touch screen is applied. Album/folder information included in the terminal is confirmed. An image file stored in the terminal is displayed on the screen of the terminal. It is determined whether a predetermined specific gesture is input with respect to the image file. When the specific gesture is input, it is determined whether the album/folder information is stored. When it is determined that the album/folder information is not stored, album/folder information is recommended. Both or one of the recommended album/folder information and the stored album/folder information is displayed on the screen of the terminal. It is determined to which album/folder information a drag is made among the album/folder information displayed on the screen of the terminal. The image file is moved to an album/folder corresponding to the album/folder information to which the drag has been made.