Abstract: A system for browsing, searching and/or viewing video content includes at least one user device and a server computer operably connected to the at least one user device. The server computer includes at least one processor operably connected to an electronic storage device, and the at least one processor is programmed with computer program instructions that, when executed, cause the server computer to present a first video on a user interface to the at least one user device, wherein the user interface presents scenes of the first video and semantic labels associated with the scenes of the first video, and wherein the user interface further presents confidence parameters associated with the scenes of the first video and the semantic labels.

Abstract: In certain embodiments, a neural network may be trained to associated context information with multimedia items. In some embodiments, context predictions for multimedia items may be obtained via a neural network. A first multimedia item and a first task related to a first context prediction for the first multimedia item may be presented on a user interface. A user response to the first task may be obtained via the user interface. Based on the user response to the first task, prediction feedback related to the first context prediction or the first multimedia item may be provided to the neural network to cause the neural network to be updated based on the prediction feedback.

Abstract: Systems and methods for browsing, searching, and/or viewing video with associated semantic labels via a user interface are presented herein. Presentation of a user interface may be effectuated. The user interface may be configured to display scenes of one or more videos and/or one or more semantic labels associated with the scenes. A first scene associated with a first video and a first semantic label associated with the first scene may be displayed in the user interface. Playback of the first video in the user interface may cause one or more changes in the display of semantic labels over time, such that responsive to playback of the first video including display of a second scene after the first scene, a second semantic label is displayed and the first semantic label is no longer displayed. The second semantic label may be associated with the second scene.

Abstract: Systems and methods for browsing, searching, and/or viewing video with associated semantic labels via a user interface are presented herein. Presentation of a user interface may be effectuated. The user interface may be configured to display scenes of one or more videos and/or one or more semantic labels associated with the scenes. A first scene associated with a first video and a first semantic label associated with the first scene may be displayed in the user interface. Playback of the first video in the user interface may cause one or more changes in the display of semantic labels over time, such that responsive to playback of the first video including display of a second scene after the first scene, a second semantic label is displayed and the first semantic label is no longer displayed. The second semantic label may be associated with the second scene.

Abstract: In certain embodiments, a neural network may be trained to associated context information with multimedia items. In some embodiments, context predictions for multimedia items may be obtained via a neural network. A first multimedia item and a first task related to a first context prediction for the first multimedia item may be presented on a user interface. A user response to the first task may be obtained via the user interface. Based on the user response to the first task, prediction feedback related to the first context prediction or the first multimedia item may be provided to the neural network to cause the neural network to be updated based on the prediction feedback.

Abstract: In certain embodiments, automated routing of media items between user devices may be facilitated. In some embodiments, a routing computer system may automatically obtain images or videos from one or more sources. The routing computer system may perform object recognition on the contents of the images or videos to identify individuals or other objects in the images or videos. The routing computer system may assign first and second images or videos of the images or videos to a first media item group based on (i) the first and second images or videos having similar metadata and (ii) the object recognition identifying an individual or object in the first image or video and an individual or object in the second image or video that are similar to each other. The routing computer system may automatically transmit the first image or video to one or more user devices based on the assignment.

Abstract: In certain embodiments, media item search and machine learning system training may be facilitated. In some embodiments, a first set of media items may be obtained (based on performance of a query) and presented on a user interface. A user selection of a media item of the first set may be obtained, and the query may be updated based on the user-selected media item. A second set of media items may be obtained based on performance of the updated query, and media items of the second set may be assigned to a group based on their similarities with one another. A predicted name for the group may be determined via a machine learning system and presented on the user interface. A user-indicated update to the predicted name for the group may be obtained and provided to the machine learning system to train the machine learning system.

Abstract: In certain embodiments, automated routing of media items between user devices may be facilitated. In some embodiments, a routing computer system may automatically obtain images or videos from one or more sources. The routing computer system may perform object recognition on the contents of the images or videos to identify individuals or other objects in the images or videos. The routing computer system may assign first and second images or videos of the images or videos to a first media item group based on (i) the first and second images or videos having similar metadata and (ii) the object recognition identifying an individual or object in the first image or video and an individual or object in the second image or video that are similar to each other. The routing computer system may automatically transmit the first image or video to one or more user devices based on the assignment.

Abstract: In certain embodiments, media item search and machine learning system training may be facilitated. In some embodiments, a first set of media items may be obtained (based on performance of a query) and presented on a user interface. A user selection of a media item of the first set may be obtained, and the query may be updated based on the user-selected media item. A second set of media items may be obtained based on performance of the updated query, and media items of the second set may be assigned to a group based on their similarities with one another. A predicted name for the group may be determined via a machine learning system and presented on the user interface. A user-indicated update to the predicted name for the group may be obtained and provided to the machine learning system to train the machine learning system.

Abstract: In certain embodiments, a neural network may be trained to associated context information with multimedia items. In some embodiments, context predictions for multimedia items may be obtained via a neural network. A first multimedia item and a first task related to a first context prediction for the first multimedia item may be presented on a user interface. A user response to the first task may be obtained via the user interface. Based on the user response to the first task, prediction feedback related to the first context prediction or the first multimedia item may be provided to the neural network to cause the neural network to be updated based on the prediction feedback.

Abstract: In certain embodiments, a neural network may be trained to associated context information with multimedia items. In some embodiments, context predictions for multimedia items may be obtained via a neural network. A first multimedia item and a first task related to a first context prediction for the first multimedia item may be presented on a user interface. A user response to the first task may be obtained via the user interface. Based on the user response to the first task, prediction feedback related to the first context prediction or the first multimedia item may be provided to the neural network to cause the neural network to be updated based on the prediction feedback.

Abstract: Systems and methods for browsing, searching, and/or viewing video with associated semantic labels via a user interface are presented herein. Presentation of a user interface may be effectuated. The user interface may be configured to display scenes of one or more videos and/or one or more semantic labels associated with the scenes. A first scene associated with a first video and a first semantic label associated with the first scene may be displayed in the user interface. Playback of the first video in the user interface may cause one or more changes in the display of semantic labels over time, such that responsive to playback of the first video including display of a second scene after the first scene, a second semantic label is displayed and the first semantic label is no longer displayed. The second semantic label may be associated with the second scene.

Abstract: Systems and methods for browsing, searching, and/or viewing video with associated semantic labels via a user interface are presented herein. Presentation of a user interface may be effectuated. The user interface may be configured to display scenes of one or more videos and/or one or more semantic labels associated with the scenes. A first scene associated with a first video and a first semantic label associated with the first scene may be displayed in the user interface. Playback of the first video in the user interface may cause one or more changes in the display of semantic labels over time, such that responsive to playback of the first video including display of a second scene after the first scene, a second semantic label is displayed and the first semantic label is no longer displayed. The second semantic label may be associated with the second scene.

Abstract: In certain embodiments, automated routing of media items between user devices may be facilitated. In some embodiments, a routing computer system may automatically obtain images or videos from one or more sources. The routing computer system may perform object recognition on the contents of the images or videos to identify individuals or other objects in the images or videos. The routing computer system may assign first and second images or videos of the images or videos to a first media item group based on (i) the first and second images or videos having similar metadata and (ii) the object recognition identifying an individual or object in the first image or video and an individual or object in the second image or video that are similar to each other. The routing computer system may automatically transmit the first image or video to one or more user devices based on the assignment.

Abstract: Systems and methods for facilitating searching, labeling, and/or filtering of digital media items are described. Users may provide queries for digital media items. Results from a search may be presented to the users. A user may provide selection of one or more displayed digital media items. A user selection may provide a digital media item exemplar that may be used to update the user-provided queries. Further searches based on the updated queries may be performed. A repository of digital media items may be queried both with an original text query supplied by a user and an updated query based user selection of digital media items returned from the original text query search. A user may be able to refine an initial text, image, and/or other query without having to know additional search terms.

Abstract: Context information may be associated with multimedia items. One or more multimedia items may be obtained from a repository, the multimedia items(s) including one or more of an image, a video, audio, a text file, combinations thereof, and/or other considerations. Predicted context information may be associated with individual ones of the multimedia items. Labels and/or other context information associated with multimedia item(s) may be stored as metadata associated with the multimedia item(s). A user interface may be configured to display one or more of the obtained multimedia items and the predicted context information associated with the one or more obtained multimedia items. Entry and/or selection may be obtained from one or more users of an addition, removal, correction, and/or confirmation of the predicted context information for individual ones of the multimedia items and/or groups of multimedia items displayed in the user interfaces.

Abstract: In certain embodiments, automated routing of media items between user devices may be facilitated. In some embodiments, a routing computer system may automatically obtain images or videos from one or more sources. The routing computer system may perform object recognition on the contents of the images or videos to identify individuals or other objects in the images or videos. The routing computer system may assign first and second images or videos of the images or videos to a first media item group based on (i) the first and second images or videos having similar metadata and (ii) the object recognition identifying an individual or object in the first image or video and an individual or object in the second image or video that are similar to each other. The routing computer system may automatically transmit the first image or video to one or more user devices based on the assignment.

Abstract: Systems and methods for facilitating the sharing of digital media items between source computing platforms and end computing platforms based on information associated with and/or derived from the media items are presented herein. Automatic routing of a media item to one or more users may be in response to obtaining digital media items, such as a photo, a video, an audio file, or text file, from one or more media item source computing platforms, obtaining information associated with individual ones of the media items, and associating one or more media items with one or more groups based on the obtained information. Other aspects of the disclosure may be related to making media items easy to locate, generating notifications to one or more users who have indicated interest in a media item and/or media item group, suggesting that a media item be shared with one or more users, and/or other features.

Abstract: A method and apparatus for permitting global roaming between two communication networks which utilize different authentication schemes. The authentication interoperability function (AIF) and method translate between the authentication schemes of each network, for example, a triplet-based network and a shared secret data (SSD) network. When a user from a network that natively uses SSD authentication roams into a triplet-based network, the authentication interoperability function produces triplets from the current SSD. When a triplet user roams into an SSD network, the AIF produces SSD from the triplet.

Abstract: Disclosed is an encrypting speech processor architecture that provides enhanced security without the use of external cryptosync and with minimal speech degradation. This is accomplished by incorporating a block encryptor and a keystream generator (instead of a fixed secret mask encryption scheme, such as those implemented in voice ciphers) for encrypting blocks of encoded speech bits at a transmitter side. The block encryptor employs an invertible cryptographic algorithm and internal cryptosync to convert a first block of encoded speech bits into a first ciphertext block. The first ciphertext block is used to generate a keystream, which is then used to encrypt a second ciphertext block.