The disclosed computer-implemented method may include generating a three-dimensional (3D) feature map for a digital image using a fully convolutional network (FCN). The 3D feature map may be configured to identify features of the digital image and identify an image region for each identified feature. The method may also include generating a region composition graph that includes the identified features and image regions. The region composition graph may be configured to model mutual dependencies between features of the 3D feature map. The method may further include performing a graph convolution on the region composition graph to determine a feature aesthetic value for each node according to the weightings in the node's weighted connecting segments, and calculating a weighted average for each node's feature aesthetic value to provide a combined level of aesthetic appeal for the digital image. Various other methods, systems, and computer-readable media are also disclosed.

In one embodiment, a method includes receiving a user request from a client system associated with a user, generating a response to the user request which references one or more entities, generating a personalized recommendation based on the user request and the response, wherein the personalized recommendation references one or more of the entities of the response, and sending instructions for presenting the response and the personalized recommendation to the client system.

Disclosed is an electronic device which includes a processor, and a memory that stores instructions and at least one images. The instructions, when executed by the processor, cause the electronic device to: classify the at least one images into at least one image group, based on meta information of the at least one image; identify tag information about at least one object of first images in a first image group of the at least one image group; identify place information about the first images, based on the tag information; and correct meta information of the first images, based on the identified place information.

Disclosed is an electronic device which includes a processor, and a memory that stores instructions and at least one images. The instructions, when executed by the processor, cause the electronic device to: classify the at least one images into at least one image group, based on meta information of the at least one image; identify tag information about at least one object of first images in a first image group of the at least one image group; identify place information about the first images, based on the tag information; and correct meta information of the first images, based on the identified place information.

An information processing system comprises an image capturing apparatus and an information processing apparatus, the image capturing apparatus includes an image capturing device; a first evaluation unit configured to perform first evaluation on a captured image; and a first transmission unit configured to transmit the captured image to the information processing apparatus, and the information processing apparatus includes a reception unit configured to receive the captured image; a second evaluation unit configured to perform second evaluation on the captured image; and a second transmission unit configured to transmit an evaluation result to the image capturing apparatus, the image capturing apparatus further including a sorting unit configured to receive the evaluation result of the second evaluation, and sort the captured image using an evaluation results of the first evaluation and the second evaluation.

Provided is a method, computer program product, and system for predicting image sharing decisions using machine learning. A processor may receive a set of annotated images and an associated text input from each user of a plurality of users. The processor may train, using the set of annotated images and the associated text input from each user, a neural network model to output an image sharing decision that is specific to a user.

Systems, methods, and other embodiments for selecting, enriching and sequencing digital media content to produce a narrative-oriented, ordered sub-collection of media such as for movie creation. The method identifies, evaluates, assesses, stores, enriches, groups, and sequences content. The method identifies the content metadata. When metadata are missing or anomalous, the method attempts to populate or correct the metadata and store that new content in the database. The method evaluates content for focus quality and may exclude content based on rules. The method assesses the content storing the people and their emotional level, animals, objects, locations, landmarks and date/time in the database. The method can then enrich the remaining content by providing map, photo, video, text, and audio content. The method uses selecting criteria for grouping and sequencing content by date, time, person, etc. and compiling the sequenced groups into the final narrative ready for distribution, e.g., movie creation.

A method in a computing device includes: in a facility containing a plurality of support structures, capturing an image of a first support structure; detecting, in the image, a first feature set of the first support structure; selecting obtaining at least one reference feature set by proximity to an estimated location of the mobile computing device in the facility coordinate system, the at least one reference feature set selected from a repository defining feature locations for each of the support structures in a facility coordinate system; comparing the first feature set with the at least one reference feature set; and in response to determining that the first feature set matches the at least one reference feature set, determining a location of the mobile computing device in the facility coordinate system based on the image and the feature locations from the repository.

Techniques are described for identifying and/or authenticating entities using a combination of independent identification technologies and/or platforms. In one embodiment, a system can comprising a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory.

The computer executable components can comprise a reception component that receives, from an entity, a request to authorize the entity based on image data of a person, wherein the request comprises the image data, and an authentication component that determines whether the person included in the image data corresponds to the entity.

Techniques are described for identifying and/or authenticating entities using a combination of independent identification technologies and/or platforms. In one embodiment, a system can comprising a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory.

The computer executable components can comprise a reception component that receives, from an entity, a request to authorize the entity based on image data of a person, wherein the request comprises the image data, and an authentication component that determines whether the person included in the image data corresponds to the entity.