Abstract: Disclosed a wiper control method and device, the method including: setting a plurality of wiper control policies, the plurality of wiper control policies at least including a control according to a detection result of a rainfall detection unit and a control according to a wiper control parameter sent by a mobile terminal; and selecting one wiper control policy to control a swing state of the wiper according to a preset condition.

Abstract: A processing unit can acquire datasets from respective data sources, each having a respective unique data domain. The processing unit can determine values of a plurality of features based on the plurality of datasets. The processing unit can modify input-specific parameters or history parameters of a computational model based on the values of the features. In some examples, the processing unit can determine an estimated value of a target feature based at least in part on the modified computational model and values of one or more reference features. In some examples, the computational model can include neural networks for several input sets. An output layer of at least one of the neural networks can be connected to the respective hidden layer(s) of one or more other(s) of the neural networks. In some examples, the neural networks can be operated to provide transformed feature value(s) for respective times.

Abstract: A processing unit can acquire datasets from respective data sources, each having a respective unique data domain. The processing unit can determine values of a plurality of features based on the plurality of datasets. The processing unit can modify input-specific parameters or history parameters of a computational model based on the values of the features. In some examples, the processing unit can determine an estimated value of a target feature based at least in part on the modified computational model and values of one or more reference features. In some examples, the computational model can include neural networks for several input sets. An output layer of at least one of the neural networks can be connected to the respective hidden layer(s) of one or more other(s) of the neural networks. In some examples, the neural networks can be operated to provide transformed feature value(s) for respective times.

Abstract: An apparatus and method is provided for near real-time, bi-layer segmentation of foreground and background portions of an image using the color and infrared images of the image. The method includes illuminating an object with infrared and visible light to produce infrared and color images of the object. An infrared mask is produced from the infrared image to predict the foreground and background portions of the image. A trimap is produced from the color image to define the color image into three distinct regions. A closed-form natural image matting algorithm is applied to the images to determine the foreground and background portions of the image.