Abstract: Systems and methods are disclosed for tracking objects in a physical environment using visual sensors onboard an autonomous unmanned aerial vehicle (UAV). In certain embodiments, images of the physical environment captured by the onboard visual sensors are processed to extract semantic information about detected objects. Processing of the captured images may involve applying machine learning techniques such as a deep convolutional neural network to extract semantic cues regarding objects detected in the images. The object tracking can be utilized, for example, to facilitate autonomous navigation by the UAV or to generate and display augmentative information regarding tracked objects to users.

Abstract: In some embodiments, an electronic device detects a first user input corresponding to a request to initiate a process to create a first sticker based on a first image including one or more objects, and facilitates creation of the sticker based on the first image. The first sticker can then be displayed in a messaging conversation.

Abstract: The present disclosure generally relates to user interfaces for altering visual media. In some embodiments, user interfaces capturing visual media (e.g., via a synthetic depth-of-field effect), playing back visual media (e.g., via a synthetic depth-of-field effect), editing visual media (e.g., that has a synthetic depth-of-field effect applied), and/or managing media capture.

Abstract: Systems and methods are disclosed for tracking objects in a physical environment using visual sensors onboard an autonomous unmanned aerial vehicle (UAV). In certain embodiments, images of the physical environment captured by the onboard visual sensors are processed to extract semantic information about detected objects. Processing of the captured images may involve applying machine learning techniques such as a deep convolutional neural network to extract semantic cues regarding objects detected in the images. The object tracking can be utilized, for example, to facilitate autonomous navigation by the UAV or to generate and display augmentative information regarding tracked objects to users.

Abstract: The present disclosure generally relates to user interfaces for altering visual media. In some embodiments, user interfaces capturing visual media (e.g., via a synthetic depth-of-field effect), playing back visual media (e.g., via a synthetic depth-of-field effect), editing visual media (e.g., that has a synthetic depth-of-field effect applied), and/or managing media capture.

Abstract: The present disclosure generally relates to user interfaces for altering visual media. In some embodiments, user interfaces capturing visual media (e.g., via a synthetic depth-of-field effect), playing back visual media (e.g., via a synthetic depth-of-field effect), editing visual media (e.g., that has a synthetic depth-of-field effect applied), and/or managing media capture.

Abstract: Systems and methods are disclosed for tracking objects in a physical environment using visual sensors onboard an autonomous unmanned aerial vehicle (UAV). In certain embodiments, images of the physical environment captured by the onboard visual sensors are processed to extract semantic information about detected objects. Processing of the captured images may involve applying machine learning techniques such as a deep convolutional neural network to extract semantic cues regarding objects detected in the images. The object tracking can be utilized, for example, to facilitate autonomous navigation by the UAV or to generate and display augmentative information regarding tracked objects to users.

Abstract: Systems and methods are disclosed for tracking objects in a physical environment using visual sensors onboard an autonomous unmanned aerial vehicle (UAV). In certain embodiments, images of the physical environment captured by the onboard visual sensors are processed to extract semantic information about detected objects. Processing of the captured images may involve applying machine learning techniques such as a deep convolutional neural network to extract semantic cues regarding objects detected in the images. The object tracking can be utilized, for example, to facilitate autonomous navigation by the UAV or to generate and display augmentative information regarding tracked objects to users.

Abstract: Systems for harnessing power through electromagnetic induction utilizing printed coils are provided. A system can include one or more moveable magnets adjacent to printed coils on a circuit. For example, a system can include one or more magnets that are operative to move alongside a circuit board that includes printed coils. The one or more magnets may move, for example, when a user shakes the system or when the user walks or runs while holding the device. The movement of the one or more magnets may create an electromotive force (e.g., a voltage) across the printed coils, and this force may be used to generate electric power.

Abstract: Systems for harnessing power through electromagnetic induction utilizing printed coils are provided. A system can include one or more moveable magnets adjacent to printed coils on a circuit. For example, a system can include one or more magnets that are operative to move alongside a circuit board that includes printed coils. The one or more magnets may move, for example, when a user shakes the system or when the user walks or runs while holding the device. The movement of the one or more magnets may create an electromotive force (e.g., a voltage) across the printed coils, and this force may be used to generate electric power.

Abstract: Systems for harnessing power through electromagnetic induction utilizing printed coils are provided. A system can include one or more moveable magnets adjacent to printed coils on a circuit. For example, a system can include one or more magnets that are operative to move alongside a circuit board that includes printed coils. The one or more magnets may move, for example, when a user shakes the system or when the user walks or runs while holding the device. The movement of the one or more magnets may create an electromotive force (e.g., a voltage) across the printed coils, and this force may be used to generate electric power.

Abstract: Systems and methods for selectively illuminating a secondary display are provided. An electronic device can include a primary display (e.g., a liquid crystal display (LCD) screen) and a printed segmented electroluminescence (secondary) display. The primary display can be used to convey visual content to a user, and the secondary display can be used to guide a user providing inputs to the device. For example, the secondary display can be selectively illuminated to provide one or more indicators that represent where or how a user can provide inputs to the device.

Abstract: Systems for harnessing power through electromagnetic induction utilizing printed coils are provided. A system can include one or more moveable magnets adjacent to printed coils on a circuit. For example, a system can include one or more magnets that are operative to move alongside a circuit board that includes printed coils. The one or more magnets may move, for example, when a user shakes the system or when the user walks or runs while holding the device. The movement of the one or more magnets may create an electromotive force (e.g., a voltage) across the printed coils, and this force may be used to generate electric power.