Abstract: A hover touch controller device includes a touch sensor having a touch surface and a proximity sensor. The touch sensor provides two-dimensional position information on when and where a user's finger touches the touch surface. The proximity sensor provides three-dimensional position information on pre-touch events. The pre-touch events corresponding to the user's finger hovering over the touch surface within some maximum depth. The hover touch controller device further includes a processor. The processor determines from the three-dimensional information a hover point projected on the touch surface and determines from the two-dimensional information a touch point on the touch surface. The processor communicates the hover point and the contact point to a display device. This can include correcting for any perceived user interaction issues associated an offset between the hover point and the touch point.

Abstract: A video editing method, apparatus and storage medium are provided. The method includes obtaining an object, the object including one or more images; determining a content element of the object for video editing, the content element having a content type identifier; determining a material set identifier corresponding to the content type identifier according to a first behavior tree logic; determining a video editing material set corresponding to the material set identifier; and obtaining an edited video according to the content element and the video editing material set.

Abstract: A welding method for manufacturing a heat sink has the following steps in sequence: removing rust from a first workpiece and a second workpiece, degreasing the first workpiece and the second workpiece, increasing surface roughness of the first workpiece and the second workpiece, performing a copper supersonic cold spray step to the first workpiece and the second workpiece, and then combining the first workpiece and the second workpiece via welding. With the copper supersonic cold spray step and the surface treatment steps before the copper supersonic cold spray step (i.e. rust removal and degreasing, and surface roughness increasing), the solder can be attached to the workpiece tightly in the combining via welding. Thus, the welded workpieces are combined firmly and not be separated easily. If a heat sink component is made through welding workpieces in the welding method, the heat sink component has higher strength and cannot be destroyed easily.

Abstract: A hover touch controller device includes a touch sensor having a touch surface with a first aspect ratio and a proximity sensor. Information on when and where a user touches the touch surface is detected. Additionally, information on hover-input events is detected. The hover input events correspond to a user's finger hovering over the touch surface within some maximum depth. The hover touch device further includes a controller. The processor communicates three-dimensional spatial information to a Graphical User Interface (GUI). The GUI generates visualizations based on the hover events and the touch events on a display having an interactive surface with a second aspect ratio. The processor further corrects for any issues associated with supporting a variety of GUI designs. This can include correcting for a difference between the first aspect ratio and the second aspect ratio.

Abstract: An electronic device for monitoring. The electronic device includes a functional module arranged to provide an active function, a communication module arranged to communicate with an external communication device, and an energy harvesting module arranged to transform a source energy from an external source to electrical energy for energising both the communication module and the functional module.

Abstract: A hover touch controller device includes a touch sensor having a touch surface with a first aspect ratio and a proximity sensor. Information on when and where a user touches the touch surface is detected. Additionally, information on hover-input events is detected. The hover input events correspond to a user's finger hovering over the touch surface within some maximum depth. The hover touch device further includes a controller. The processor communicates three-dimensional spatial information to a Graphical User Interface (GUI). The GUI generates visualizations based on the hover events and the touch events on a display having an interactive surface with a second aspect ratio. The processor further corrects for any issues associated with supporting a variety of GUI designs. This can include correcting for a difference between the first aspect ratio and the second aspect ratio.

Abstract: A hover touch controller device includes a touch sensor having a touch surface and a proximity sensor. The touch sensor provides two-dimensional position information on when and where a user's finger touches the touch surface. The proximity sensor provides three-dimensional position information on pre-touch events. The pre-touch events corresponding to the user's finger hovering over the touch surface within some maximum depth. The hover touch controller device further includes a processor. The processor determines from the three-dimensional information a hover point projected on the touch surface and determines from the two-dimensional information a touch point on the touch surface. The processor communicates the hover point and the contact point to a display device. This can include correcting for any perceived user interaction issues associated an offset between the hover point and the touch point.

Abstract: A controller includes a touch sensor and a proximity sensor. Information on when and where a user touches the surface of the touch sensor is detected. Additionally, information on pre-touch events is detecting. The pre-touch events correspond to a user's finger hovering over the touch sensor within some maximum depth. A display device generates visualizations based on the hover events and the touch events. This can include providing visual feedback in a hover mode where a user's finger is, relative to the touch sensor. Additionally, various forms of navigation information may be provided in the hover mode, as well as other control information.

Abstract: An electronic device includes a touchscreen display and at least one processor. The at least one processor is configured to present a dynamic user interface on the touchscreen display. The dynamic user interface includes a first input region forming a dial. The first input region is configured to receive user input related to a first viewing direction associated with a 360° video. The at least one processor is also configured to detect the user input. In addition, the at least one processor is configured to transmit the user input to a display device to control presentation of the 360° video on the display device. The dynamic user interface may further include a second input region, where the second input region is configured to receive second user input related to a second viewing direction associated with the 360° video.

Abstract: A method includes retrieving, by a device, contextual information based on at least one of an image, the device, user context, or a combination thereof. At least one model is identified from multiple models based on the contextual information and at least one object recognized in an image based on at least one model. At least one icon is displayed at the device. The at least one icon being associated with at least one of an application, a service, or a combination thereof providing additional information.

Abstract: Embodiments of this application provide a neural network model deployment method, a prediction method and a device. The described features can implement deployment of a neural network model to improve the universality of the deployment of the neural network model to the terminal device by obtaining a layer definition and an operation parameter of each network layer of an initial neural network model, executing a target network layer corresponding to the network layers, applying relational connections amongst the target network layers using a net class, converting the operation parameters into a preset format, obtaining a target operation parameter based on the preset format, loading a corresponding target operation parameter in the target network layer, and obtaining a target neural network model based on the target operation parameter.

Abstract: A method includes retrieving, by a device, contextual information based on at least one of an image, the device, user context, or a combination thereof. At least one model is identified from multiple models based on the contextual information and at least one object recognized in an image based on at least one model. At least one icon is displayed at the device. The at least one icon being associated with at least one of an application, a service, or a combination thereof providing additional information.

Abstract: A method of managing a plurality of devices is described. The method comprises receiving an image comprising the plurality of devices; determining, based on an analysis of the image, a spatial map for the plurality of devices, wherein the spatial map comprises, for each device of the plurality of devices, a position relative to another device of the plurality of devices; and adjusting a sensor of at least one of the plurality of devices to modify an acoustic field associated with the plurality of devices based on the spatial map. A system for providing information is also described.

Abstract: A method includes receiving a voice input at an electronic device. An ambiguity of the voice input is determined. The ambiguity is resolved based on contextual data. The contextual data includes at least one of: an image, a non-voice input comprising a gesture, a pointer of a pointing device, a touch, or a combination thereof.

Abstract: A controller includes a touch sensor and a proximity sensor. Information on when and where a user touches the surface of the touch sensor is detected. Additionally, information on pre-touch events is detecting. The pre-touch events correspond to a user's finger hovering over the touch sensor within some maximum depth. A display device generates visualizations based on the hover events and the touch events. This can include providing visual feedback in a hover mode where a user's finger is, relative to the touch sensor. Additionally, various forms of navigation information may be provided in the hover mode, as well as other control information.

Abstract: Face detection techniques are provided that use a multiple-stage face detection algorithm. An exemplary three-stage algorithm includes a first stage that applies linear-filtering to enhance detection performance by removing many non-face-like portions within an image, a second stage that uses a boosting chain that is adopted to combine boosting classifiers within a hierarchy “chain” structure, and a third stage that performs post-filtering using image pre-processing, SVM-filtering and color-filtering to refine the final face detection prediction. In certain further implementations, the face detection techniques include a two-level hierarchy in-plane pose estimator to provide a rapid multi-view face detector that further improves the accuracy and robustness of face detection.

Abstract: A novel statistical learning procedure that can be applied to many machine-learning applications is presented. Although this boosting learning procedure is described with respect to its applicability to face detection, it can be applied to speech recognition, text classification, image retrieval, document routing, online learning and medical diagnosis classification problems.

Abstract: A novel statistical learning procedure that can be applied to many machine-learning applications is presented. Although this boosting learning procedure is described with respect to its applicability to face detection, it can be applied to speech recognition, text classification, image retrieval, document routing, online learning and medical diagnosis classification problems.

Abstract: A novel statistical learning procedure that can be applied to many machine-learning applications is presented. Although this boosting learning procedure is described with respect to its applicability to face detection, it can be applied to speech recognition, text classification, image retrieval, document routing, online learning and medical diagnosis classification problems.

Abstract: A novel statistical learning procedure that can be applied to many machine-learning applications is presented. Although this boosting learning procedure is described with respect to its applicability to face detection, it can be applied to speech recognition, text classification, image retrieval, document routing, online learning and medical diagnosis classification problems.