Abstract:
Certain embodiments of the disclosed technology include systems and methods for determining the priority of a notification on a mobile device using machine learning. Other aspects of the disclosed technology include selectively displaying notifications based on the priority of a notification. According to an embodiment of the disclosed technology, a computer-implement method is provided that comprises outputting, to a display device operatively coupled to a mobile device, a plurality of notifications, wherein each respective notification from the plurality of notifications is associated with a respective priority score; modifying, by the mobile device, a ranking model based on a user input received responsive to a first notification from the plurality of notifications and a characteristic of a second notification from the plurality of notifications; determining, by the mobile device, a priority score associated with a third notification based on the modified ranking model; and outputting, to the display device, the third notification based on the priority score associated with the third notification, wherein the third notification is graphically emphasized responsive to the priority score associated with the third notification being greater than at least one respective priority score associated with a corresponding respective notification from the plurality of notifications.
Abstract:
Techniques for determining motion saliency in video content using center-surround receptive fields. In some implementations, images or frames from a video may be apportioned into non-overlapped regions, for example, by applying a rectilinear grid. For each grid region, or cell, motion consistency may be measured between the center and surround area of that cell across frames of the video. Consistent motion across the center-surround area may indicate that the corresponding region has low variation. The larger the difference between center-surround motions in a cell, the more likely the region has high motion saliency.
Abstract:
Techniques for determining motion saliency in video content using center-surround receptive fields. In some implementations, images or frames from a video may be apportioned into non-overlapped regions, for example, by applying a rectilinear grid. For each grid region, or cell, motion consistency may be measured between the center and surround area of that cell across frames of the video. Consistent motion across the center-surround area may indicate that the corresponding region has low variation. The larger the difference between center-surround motions in a cell, the more likely the region has high motion saliency.
Abstract:
A video hosting service comprising video classifiers that identify content sources of content included in videos uploaded to the video hosting service. Identifying the content source allows a content owner of the content source to claim ownership of videos that include content based on the content source. Usage policies associated with the content owners are applied to the uploaded videos that describe how the video hosting service is to treat the videos.
Abstract:
Certain embodiments of the disclosed technology include systems and methods for determining the priority of a notification on a mobile device using machine learning. Other aspects of the disclosed technology include selectively displaying notifications based on the priority of a notification. According to an embodiment of the disclosed technology, a computer-implement method is provided that comprises outputting, to a display device operatively coupled to a mobile device, a plurality of notifications, wherein each respective notification from the plurality of notifications is associated with a respective priority score; modifying, by the mobile device, a ranking model based on a user input received responsive to a first notification from the plurality of notifications and a characteristic of a second notification from the plurality of notifications; determining, by the mobile device, a priority score associated with a third notification based on the modified ranking model; and outputting, to the display device, the third notification based on the priority score associated with the third notification, wherein the third notification is graphically emphasized responsive to the priority score associated with the third notification being greater than at least one respective priority score associated with a corresponding respective notification from the plurality of notifications.