Abstract: A system and method for detecting, recording and communicating events involved in the care and treatment of cognitively impaired persons through detection, video recording, storage and communication. The system includes video cameras that typically begin recording upon detecting motion, a local computing unit at the care location that detects alerts, and a cloud or other remote computing and transmission unit. The local computing unit aggregates, stores, processes, and transmits data including performing event detection through an artificial intelligence technique and generating appropriate alerts. The cloud computing aggregates data from many managed care communities, trains new convolutional neural networks from this data, distributes these networks to the local computing units to perform event detection, and provides a platform for various stakeholders to view the collected video data and generated alerts.

Abstract: A method of wireless power sharing includes initiating a wireless power sharing session; mutually authenticating a first electronic device with a second electronic device wirelessly; determining, a physical disposition of the first electronic device or the second electronic device as a part of the wireless power sharing session; computing a power profile and transferring wirelessly the power profile; identifying a plurality of computational resources eligible for a handover based on artificial intelligence techniques and the power profile; and transferring an information wirelessly for triggering a handover of the plurality of computational resources, wherein the transferring is defined as at least one of: transferring of the information of the plurality of computational resources from the first electronic device to the second electronic device; or transferring of the information of the plurality of computational resources from the second electronic device to the first electronic device.

Abstract: A system and method for detecting, recording and communicating events involved in the care and treatment of cognitively impaired persons through detection, video recording, storage and communication. The system includes video cameras that typically begin recording upon detecting motion, a local computing unit at the care location that detects alerts, and a cloud or other remote computing and transmission unit. The local computing unit aggregates, stores, processes, and transmits data including performing event detection through an artificial intelligence technique and generating appropriate alerts. The cloud computing aggregates data from many managed care communities, trains new convolutional neural networks from this data, distributes these networks to the local computing units to perform event detection, and provides a platform for various stakeholders to view the collected video data and generated alerts.

Abstract: A system and method for detecting, recording and communicating events involved in the care and treatment of cognitively impaired persons through detection, video recording, storage and communication. The system includes video cameras that typically begin recording upon detecting motion, a local computing unit at the care location that detects alerts, and a cloud or other remote computing and transmission unit. The local computing unit aggregates, stores, processes, and transmits data including performing event detection through an artificial intelligence technique and generating appropriate alerts. The cloud computing aggregates data from many managed care communities, trains new convolutional neural networks from this data, distributes these networks to the local computing units to perform event detection, and provides a platform for various stakeholders to view the collected video data and generated alerts.

Abstract: A system and method for detecting, recording and communicating events involved in the care and treatment of cognitively impaired persons through detection, video recording, storage and communication. The system includes video cameras that typically begin recording upon detecting motion, a local computing unit at the care location that detects alerts, and a cloud or other remote computing and transmission unit. The local computing unit aggregates, stores, processes, and transmits data including performing event detection through an artificial intelligence technique and generating appropriate alerts. The cloud computing aggregates data from many managed care communities, trains new convolutional neural networks from this data, distributes these networks to the local computing units to perform event detection, and provides a platform for various stakeholders to view the collected video data and generated alerts.

Abstract: A system and method for detecting, recording and communicating events involved in the care and treatment of cognitively impaired persons through detection, video recording, storage and communication. The system includes video cameras that typically begin recording upon detecting motion, a local computing unit at the care location that detects alerts, and a cloud or other remote computing and transmission unit. The local computing unit aggregates, stores, processes, and transmits data including performing event detection through an artificial intelligence technique and generating appropriate alerts. The cloud computing aggregates data from many managed care communities, trains new convolutional neural networks from this data, distributes these networks to the local computing units to perform event detection, and provides a platform for various stakeholders to view the collected video data and generated alerts.

Abstract: A method includes determining a training scale for training a machine-learning model, defining a group of worker nodes having a number of worker nodes that is selected according to the training scale, and determining an average gradient of a loss function during a training iteration using the group of worker nodes. The method also includes determining a variance value for the average gradient of the loss function, determining a gain ratio based on the variance value for the average gradient of the loss function, and determining a learning rate parameter based on a learning rate schedule and the gain ratio. The method also includes determining updated parameters for the machine-learning model using the learning rate parameter and the average gradient of the loss function.

Abstract: Embodiments herein provide a method for capturing view in an electronic device comprising at least two image sensors. The method includes determining a folding angle between a first side of the electronic device including a first image sensor and a second side of the electronic device including a second image sensor. Further, the method also includes capturing a first view of a scene using the first image sensor and capturing a second view of the scene using the second image sensor. Further, the method includes determining whether the first view and the second view partially overlap with each other, completely overlap with each other, or do not overlap with each other based on the folding angle.

Abstract: The subject technology generates a dataset based at least in part on a set of files. The subject technology generates, utilizing a machine learning model, a set of labels corresponding to the dataset. The subject technology filters the dataset using a set of conditions to generate at least a subset of the dataset. The subject technology generates a virtual object based at least in part on the subset of the dataset and the set of labels, where the virtual object corresponds to a selection of data from the dataset. The subject technology trains a second machine learning model using the virtual object and at least the subset of the dataset, where training the second machine learning model includes utilizing streaming file input/output (I/O), the streaming file I/O providing access to at least the subset of the dataset during training.

Abstract: Embodiments herein provide a method for capturing view in an electronic device comprising at least two image sensors. The method includes determining a folding angle between a first side of the electronic device including a first image sensor and a second side of the electronic device including a second image sensor. Further, the method also includes capturing a first view of a scene using the first image sensor and capturing a second view of the scene using the second image sensor. Further, the method includes determining whether the first view and the second view partially overlap with each other, completely overlap with each other, or do not overlap with each other based on the folding angle.

Abstract: Embodiments herein provide a method and electronic device for managing accessory application of accessory device by companion device. The method includes identifying the at least one pre-determined feature of the accessory application running at the accessory device. Further, the method includes generating the application package comprising the at least one component of the at least one pre-determined feature of the accessory application and transferring the application package to a companion device to perform at least one operation corresponding to the at least one pre-determined feature of the accessory application at the companion device on behalf of the accessory device.

Abstract: A system and method for detecting, recording and communicating events involved in the care and treatment of cognitively impaired persons through detection, video recording, storage and communication. The system includes video cameras that typically begin recording upon detecting motion, a local computing unit at the care location that detects alerts, and a cloud or other remote computing and transmission unit. The local computing unit aggregates, stores, processes, and transmits data including performing event detection through an artificial intelligence technique and generating appropriate alerts. The cloud computing aggregates data from many managed care communities, trains new convolutional neural networks from this data, distributes these networks to the local computing units to perform event detection, and provides a platform for various stakeholders to view the collected video data and generated alerts.

Abstract: A method for transferring data items in an electronic device is provided. The method includes associating a function and a data item with an identifier based on a user action performed in a source location, and performing the function to transfer the data item from the source location to a target location based on the user action performed on the identifier in the target location.

Abstract: Methods and devices for dynamically reconfiguration of user interface on a touch device (100) are described. The touch device (100) includes a touch-screen (108) to receive a user swipe input (202) from a user. Thereafter, the touch device (100) determines a user-touchable area based on the user swipe input (202). Based on a reconfiguration setting, the user interface is reconfigured on the touch-screen (108) within the user-touchable area.

Abstract: A method for generating a histogram in a spiking neural network includes counting spikes associated with a latency encoded representation of an object. The method also includes generating the histogram based on the spike count.

Abstract: A method for invariantly representing an object using a spiking neural network includes representing the object by a spike sequence. The method also includes determining a reference feature of the object representation. The method further includes transforming the object representation to a canonical form based on the reference feature.