Abstract: A system of machine learning schemes can be configured to efficiently perform image processing tasks on a user device, such as a mobile phone. The system can selectively detect and transform individual regions within each frame of a live streaming video. The system can selectively partition and toggle image effects within the live streaming video.

Abstract: A compact generative neural network can be distilled from a teacher generative neural network using a training network. The compact network can be trained on the input data and output data of the teacher network. The training network train the student network using a discrimination layer and one or more types of losses, such as perception loss and adversarial loss.

Abstract: Systems and methods for object-based content recommendation are described. A camera feed comprising a plurality of image frames is caused to be displayed at a client device. An object is detected within an image frame from the camera feed, the object corresponding with an object category. Responsive to detecting the object, an icon associated with the object category is selected and displayed at a position upon the camera feed. The icon corresponds with a media collection related to the object category. An input is received selecting the icon. Responsive to the input, a presentation of media items from the media collection is displayed at the client device. By detecting real-world objects and surfacing relevant virtual icons that link to associated media, an augmented reality experience is provided allowing virtual content to be overlaid and anchored to objects in reality.

Abstract: A compact generative neural network can be distilled from a teacher generative neural network using a training network. The compact network can be trained on the input data and output data of the teacher network. The training network train the student network using a discrimination layer and one or more types of losses, such as perception loss and adversarial loss.

Abstract: A system of machine learning schemes can be configured to efficiently perform image processing tasks on a user device, such as a mobile phone. The system can selectively detect and transform individual regions within each frame of a live streaming video. The system can selectively partition and toggle image effects within the live streaming video.

Abstract: A compact generative neural network can be distilled from a teacher generative neural network using a training network. The compact network can be trained on the input data and output data of the teacher network. The training network train the student network using a discrimination layer and one or more types of losses, such as perception loss and adversarial loss.

Abstract: A system of machine learning schemes can be configured to efficiently perform image processing tasks on a user device, such as a mobile phone. The system can selectively detect and transform individual regions within each frame of a live streaming video. The system can selectively partition and toggle image effects within the live streaming video.

Abstract: A compact generative neural network can be distilled from a teacher generative neural network using a training network. The compact network can be trained on the input data and output data of the teacher network. The training network train the student network using a discrimination layer and one or more types of losses, such as perception loss and adversarial loss.

Abstract: A system of machine learning schemes can be configured to efficiently perform image processing tasks on a user device, such as a mobile phone. The system can selectively detect and transform individual regions within each frame of a live streaming video. The system can selectively partition and toggle image effects within the live streaming video.

Abstract: A system of machine learning schemes can be configured to efficiently perform image processing tasks on a user device, such as a mobile phone. The system can selectively detect and transform individual regions within each frame of a live streaming video. The system can selectively partition and toggle image effects within the live streaming video.

Abstract: A compact generative neural network can be distilled from a teacher generative neural network using a training network. The compact network can be trained on the input data and output data of the teacher network. The training network train the student network using a discrimination layer and one or more types of losses, such as perception loss and adversarial loss.

Abstract: A compact generative neural network can be distilled from a teacher generative neural network using a training network. The compact network can be trained on the input data and output data of the teacher network. The training network train the student network using a discrimination layer and one or more types of losses, such as perception loss and adversarial loss.

Abstract: Systems and methods for identifying trends in web feeds collected from various content servers are disclosed. One embodiment includes, selecting a candidate phrase indicative of potential trends in the web feeds, assigning the candidate phrase to trend analysis agents, analyzing the candidate phrase, by each of the one or more trend analysis agents, respectively using the configured type of trending parameter, and/or determining, by each of the trend analysis agents, whether the candidate phrase meets an associated threshold to qualify as a potential trended phrase.

Abstract: Systems and methods for identifying trends in web feeds collected from various content servers are disclosed. One embodiment includes, selecting a candidate phrase indicative of potential trends in the web feeds, assigning the candidate phrase to trend analysis agents, analyzing the candidate phrase, by each of the one or more trend analysis agents, respectively using the configured type of trending parameter, and/or determining, by each of the trend analysis agents, whether the candidate phrase meets an associated threshold to qualify as a potential trended phrase.

Abstract: A multi-layered microcapsule has an inner extracellular matrix and an outer shell. The inner extracellular matrix includes a first inner layer of biopolymer and a second intermediate layer of polymer that provides partial immune-protection and holds the first layer in place. The outer shell can form an exoskeleton to provide mechanical stability. Each of the individual layers can be varied to optimize mechanical stability, cell function, and immuno-protection.