Guangdong Oppo Mobile Telecommunications Corp., Ltd.

Yaoyong Liu

Yan Chen

Meirong Ma

A method for gender recognition of a user and related products are provided. The method includes the following. A sever receives user characteristic data from a mobile terminal, where the user characteristic data is indicative of usage of the mobile terminal by the user. At least one user characteristic data sample matching the user characteristic data is determined from a predetermined set of user characteristic data samples. At least one reference gender corresponding to the at least one user characteristic data sample is obtained by querying a preset correspondence between user characteristic data samples and reference genders. Gender of the user is determined according to the at least one reference gender and the gender determined is sent to the mobile terminal.

Method for gender recognition of user and related products

A photographing method and device, a storage medium and an electronic apparatus are disclosed. The method includes the following. A current photographing scene is determined based on a current preview image. Based on the current photographing scene, pre-stored historical adjustment information of a photographing parameter matching the current photographing scene is acquired. Current adjustment information is determined based on the historical adjustment information. Adjustment is performed on the current preview image on the basis of the current adjustment information, and an adjusted current preview image is output.

Photographing method and device, and related electronic apparatus

A method for establishing an application prediction model, a storage medium, and a terminal are provided. The method includes the following. In response to an operation switching an application previously running in the foreground to a first application currently running, a first preorder usage sequence of the first application currently running is collected as sample usage information. Applications launched within a time-window are monitored, and a preset number of applications launched first in the applications launched within the time-window are set as sample labels for the sample usage information. A predetermined machine learning model is trained based on the sample usage information and the sample labels for the sample usage information, to obtain the application prediction model.

Method for establishing applications-to-be preloaded prediction model based on preorder usage sequence of foreground application, storage medium, and terminal

A method and device for blurring an image background, a storage medium, and an electronic apparatus. The method for blurring an image background comprises: using a preset classification model to divide an image to be processed into a foreground region and a background region (); detecting a contour edge of a photographic subject in the foreground region obtained from the division (S); and performing blurring on a background of the image according to the contour edge of the photographic subject (S).

Method and device for blurring image background, storage medium and electronic apparatus

A method for preloading an application, a storage medium, and a terminal are provided. The method includes the following. Current usage information of a terminal is acquired in response to detecting that an event of prediction of preloading an application is triggered. The current usage information is input to a model used for application prediction. The model used for application prediction includes a hybrid network model generated according to a usage rule of applications of the terminal corresponding to historical status feature information. At least one target application to be launched is predicted according to an output result of the model used for application prediction. The at least one target application is preloaded.

Method for preloading application, storage medium, and terminal

An image processing method, an apparatus, a storage medium, and an electronic device are provided. The image processing method comprises: identifying a human face area in a target image (); determining a local area to be processed from the human face area on the basis of a trained convolutional neural network model (); obtaining posture information of a human face in the target image (); selecting a target sample human face image from a human face image data base according to the posture information (); and correcting the local area according to the target sample human face image ().

Image processing method, apparatus, storage medium, and electronic device

A video producing method, an apparatus, a storage medium, and an electronic device. The video producing method comprises: acquiring keywords configured by a user, the keywords comprising a participant and a participation event; determining a plurality of photographing tasks according to the keywords, and a trigger condition of each of the photographing tasks; prompting, according to the trigger condition, the user to perform the corresponding photographing task, to obtain at least one photo; and generating a video file according to the at least one photo.

Video producing method, apparatus, storage medium, and electronic device

A method for processing an image is provided. The method includes that: a preview image to be processed is acquired; scene information is identified from the preview image; a composition mode corresponding to the scene information is determined; and the preview image is composed according to the composition mode. A device for processing an image and a mobile terminal are also provided.

Method and device for processing image, and mobile terminal

A method for preloading an application, a storage medium, and a terminal device are provided. The method includes the following. Current state feature information of the terminal device is acquired, when an application preloading prediction event is detected to be triggered. The current state feature information is input into a plurality of CART prediction models each corresponding to an application in a preset application set, where each of the CART prediction models is generated based on a usage regularity of an associated application corresponding to historical state feature information of the terminal device. A target application to be initiated is predicted according to output results of the CART prediction models, and then the target application is preloaded.

Method for preloading application, storage medium, and terminal device

Provided are a method and apparatus for training a classification model, a mobile terminal, and a computer-readable storage medium. The method includes that: a classification model is trained based on a preset data set until the accuracy of the classification model reaches a standard value, wherein data in the preset data set includes label information; data in the preset data set is identified based on the trained classification model to acquire category information of the data; when the category information of the data is not matched with the label information, the data is cleaned to acquire a cleaned target data set; and the classification model is trained again based on the target data set.

Method and apparatus for training, classification model, mobile terminal, and readable storage medium

A method for preloading an application, a storage medium, and a terminal are provided. The method includes the following. An application to be preloaded is determined in response to detecting that an event of application preloading is triggered. When a new application installed within a time-window exists, whether the new application belongs to the application to be preloaded is determined. The new application and the application to be preloaded are preloaded based on a determination that the new application does not belong to the application to be preloaded.

The embodiment of the disclosure discloses a method and an apparatus for image processing, and a mobile terminal. The method may include: acquiring image parameters of a real-time preview image displayed in a preview interface; evaluating, based on the image parameters and a pre-established image evaluation model, the real-time preview image to obtain an evaluation result; and displaying the evaluation result. The method enables the user of the mobile terminal to obtain the evaluation result of the real-time preview image displayed in the preview interface in real time, so that the user can get the quality of the current real-time preview image in real time, and the user can adjust the real-time preview image as needed, in order to obtain images with better evaluation results, thereby improving the overall quality of the images captured by the mobile terminal.

Image processing method and mobile terminal

A method for preloading an application, a storage medium, and a terminal device are provided. The method includes the following. In response to a target application being detected to be closed, current state feature information of a terminal device is acquired. The current state feature information is input into a random forest prediction model corresponding to the target application, where the random forest prediction model is generated based on a usage regularity of the target application corresponding to historical state feature information of the terminal device. Whether to preload the target application is determined according to a prediction result of the random forest prediction model.

Method for preloading application, computer readable storage medium, and terminal device

A method for preloading an application, a storage medium, and a terminal device are provided. The method includes the following. In response to a target application being detected to be closed, current state feature information of a terminal device is acquired. The current state feature information is compared with historical state feature information of the terminal device when the target application was closed. Target historical state feature information closest to the current state feature information is determined from within the historical state feature information according to a comparison result. The target application is preloaded, in response to determining that the target application is about to be launched again according to a historical usage regularity corresponding to the target historical state feature information.

Method and device for preloading application, storage medium, and terminal device

A method for preloading an application, a storage medium, and a terminal device are provided. The method includes the following. First status feature information of a terminal device is acquired in response to an application-preloading-prediction event being detected to be triggered. The first status feature information is compared with a plurality of pre-collected samples of a sample set. The plurality of pre-collected samples include status second feature information of the terminal device in a preset sampling period, and each sample of the plurality of pre-collected samples corresponds to a sample tag indicating a next application to be launched. A target application to be launched is predicted according to a comparison result. The target application is preloaded.

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Guangdong, China

Yaoyong Liu