Journey information is mapped by first identifying an acceptable trigger condition type, such as a photo trigger condition type, of a plurality of trigger condition types. Once a journey has begun, a trigger condition of the acceptable trigger condition type may be detected at a mobile computing device, for example when the mobile computing device captures a photo. A location of the mobile computing device is then identified in response to the detection of the trigger condition, and a marker is placed on a map identifying the location. The marker is also associated with data associated with the trigger condition, for example by allowing the photo captured by the mobile computing device to be viewable at the marker.

Journey information is mapped by first identifying an acceptable trigger condition type, such as a photo trigger condition type, of a plurality of trigger condition types. Once a journey has begun, a trigger condition of the acceptable trigger condition type may be detected at a mobile computing device, for example when the mobile computing device captures a photo. A location of the mobile computing device is then identified in response to the detection of the trigger condition, and a marker is placed on a map identifying the location. The marker is also associated with data associated with the trigger condition, for example by allowing the photo captured by the mobile computing device to be viewable at the marker.

A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include determining a ranking of images using a machine learning system. The machine learning system is trained using attributes that represent each of a plurality of training images. The attributes include imagery attributes, social network attributes, and textual attributes. Operations also include producing a listing of the ranked images for selecting one or more of the ranked images for a brand entity associated with the selected ranked images.

A system includes a computing device that includes a memory configured to store instructions. The system also includes a processor to execute the instructions to perform operations that include determining a ranking of images using a machine learning system. The machine learning system is trained using attributes that represent each of a plurality of training images. The attributes include imagery attributes, social network attributes, and textual attributes. Operations also include producing a listing of the ranked images for selecting one or more of the ranked images for a brand entity associated with the selected ranked images.

An operation method for generating content including a user identification (ID), and an apparatus therefor are provided. The operation method of the device includes obtaining mapping information by making one or more pieces of biometric information for each of a plurality of users correspond to a user ID of each of the plurality of users, obtaining first content including a first user by photographing the first user, obtaining first biometric information of the first user, determining a first user ID corresponding to the first biometric information of the first user, based on the mapping information, and associating the first content with the first user ID, and storing the association of the first content with the first user ID.

The present disclosure provides a system for a user to upload a photo of an image object and an associated question related to the image object. If the system can determine a direct match based on previously stored image objects in a database correctly, the user can verify that the system generated answer is correct. If the system cannot identify the image object from the database, the system can rely on other users of the application to help identify and comment on the image object to determine the answers to the user's questions about the image object.

A system for automated conversion and delivery of medical images. In an example implementation, a server is configured to retrieve a medical image file including medical data and metadata, in a medical data format, determine an output destination type based on the metadata, identify standardized format specifications based on the determined output destination type from the retrieved metadata, convert the medical data into a format compatible with the identified standardized format, and transmit an output message of the converted medical data to at least a recipient delivery address.

Methods, systems, and apparatus for receiving a query image, receiving one or more entities that are associated with the query image, identifying, for one or more of the entities, one or more candidate search queries that are pre-associated with the one or more entities, generating a respective relevance score for each of the candidate search queries, selecting, as a representative search query for the query image, a particular candidate search query based at least on the generated respective relevance scores and providing the representative search query for output in response to receiving the query image.

A device for organizing digital files is provided, wherein tagging data is applied to a sequence of image files previously captured by and received from an imaging device. A tagging image having tagging data therein is preferably provided before or after the sequence, or both. A text recognizing technology may be used to extract the tagging data from a tagging image. For example, if a tagging image is taken on a camera prior to a sequence of images, the device may extract tagging data from the tagging image and apply such tagging data to the sequence of image files. Preferably, the device provides for renaming of the image files utilizing the tagging data.

Systems, methods, devices, media, and computer-readable instructions are described for local image tagging and processing in a resource-constrained environment such as a mobile device. In some embodiments, characteristics associated with images are used to determine whether to store content (e.g., images and video clips) as ephemeral content or non-ephemeral content. Based on the determination, the image is stored in a non-ephemeral camera roll storage of the mobile device, or an ephemeral local application storage. Additional storage operations such as encryption or backup copying may additionally be determined and performed based on the analysis of the content. In some embodiments, such images may be indexed, sorted, and searched based on the image tagging operations used to characterize the content.