Abstract: A device control method is provided. In the method, a first message is received from a first device of a device messaging group. The first device is associated with a first identifier in the device messaging group. The first message indicates at least one of a state of the first device or detected environment information. A second message is generated based on the first message received from the first device. The second message is sent to a second device of the device messaging group. The second device is associated with a second identifier in the device messaging group.

Abstract: In a form generation method, a text entry interface is displayed. The text entry interface is configured to receive text content of a plurality of questions to be included in a questionnaire form. The text content of the plurality of questions to be included in the questionnaire form and entered in the text entry interface is received. The questionnaire form is generated according to the text content. The questionnaire form includes a plurality of questions that are determined based on parsing of the text content. Further, the questionnaire form is displayed.

Abstract: A method for microscope-based super-resolution includes acquiring a to-be-processed image and at least an auxiliary image, the to-be-processed image includes a target area, the auxiliary image includes an overlapping portion with the target area, and the to-be-processed image and the auxiliary image are both microscope images of a first resolution. The method further includes registering the to-be-processed image and the auxiliary image to obtain a registered image, and extracting one or more high-resolution features from the registered image. The one or more high-resolution features represent image features of the target area in a second resolution, and the second resolution is greater than the first resolution. The method also includes reconstructing, based on the one or more high-resolution features, a target image of the second resolution corresponding to the to-be-processed image of the first resolution.

Abstract: The present disclosure provides a security verification method and a relevant device, to increase the difficulty of cracking. The method includes: receiving, from a verification requester, a request for pulling a sliding verification code; acquiring the sliding verification code which includes a slider and a second endpoint image obtained by performing filter processing on a first endpoint image; and returning the sliding verification code to the verification requester. The first endpoint image and the slider are generated from the same original image, and the slider and the second endpoint image are returned to the verification requester finally. The second endpoint image is obtained by performing image processing on the first endpoint image, and after the image processing, in an area outside the slider placement area, pixel values of pixels in the second endpoint image are different from pixel values of corresponding pixels in the original image.

Abstract: Embodiments of this application include an information conversion method for translating source information. The source information is encoded to obtain a first code. A preset conversion condition is obtained. The preset conversion condition indicates a mapping relationship between the source information and a conversion result. The first code is decoded according to the source information, the preset conversion condition, and translated information to obtain target information. The target information and the source information are in different languages. Further, the translated information includes a word obtained through conversion of the source information into a language of the target information.

Abstract: A communication method is provided. The method includes transmitting a network address assignment request to the network address translation entity after establishing a general packet radio service (GPRS) tunneling protocol (GTP) tunnel between the first user-plane function entity and the second user-plane function entity, such that the network address translation entity assigns a network address to the GTP tunnel, notifying the network address assigned by the network address translation entity to the GTP tunnel to the central data network, controlling a data packet to be transmitted by the edge service node to the central data network to be transmitted through the GTP tunnel, the network address translation entity replacing a source address of the data packet with the network address, and transmitting the data packet to the central data network after the data packet arrives at the network address translation entity.

Abstract: The present disclosure describes human body attribute recognition methods and apparatus, electronic devices, and a storage medium. The method includes acquiring a sample image containing a plurality of to-be-detected areas being labeled with true values of human body attributes; generating, through a recognition model, a heat map of the sample image and heat maps of the to-be-detected areas to obtain a global heat map and local heat maps; fusing the global and the local heat maps to obtain a fused image, and performing human body attribute recognition on the fused image to obtain predicted values; determining a focus area of each type of human body attribute according to the global and the local heat maps; correcting the recognition model by using the focus area, the true values, and the predicted values; and performing, based on the corrected recognition model, human body attribute recognition on a to-be-recognized image.

Abstract: An audio data processing method is provided. The method includes: obtaining multi-path audio data in an environmental space, obtaining a speech data set based on the multi-path audio data, and separately generating, in a plurality of enhancement directions, enhanced speech information corresponding to the speech data set; matching a speech hidden feature in the enhanced speech information with a target matching word, and determining an enhancement direction corresponding to the enhanced speech information having a highest degree of matching with the target matching word as a target audio direction; obtaining speech spectrum features in the enhanced speech information, and obtaining, from the speech spectrum features, a speech spectrum feature in the target audio direction; and performing speech authentication on the speech hidden feature and the speech spectrum feature that are in the target audio direction based on the target matching word, to obtain a target authentication result.

Abstract: A content presenting method includes: starting a 3D application, in response to an instruction, a 3D application presenting a simulated object of an end user and a virtual screen for displaying live content in a virtual environment; receiving a content source address of the live content that is provided by another user equipment on an anchor to a content providing server, and that is currently broadcasted on the content providing server; obtaining audio data and video data of the live content from the content providing server, based on the content source address; rendering the audio data and the video data to obtain video content and audio content; playing the audio content in the 3D application; obtaining content of interaction between the anchor of the video content displayed using the virtual screen and the simulated object; and displaying the video content and the content of interaction on the virtual screen.

Abstract: The present disclosure discloses a method, apparatus, and server for information recommendation. Search behavior data, browsing behavior data, and click behavior data on recommended content of a specified user in a forum are acquired. A preprocessing on the search behavior data, the browsing behavior data, and the click behavior data on recommended content is performed respectively to obtain a first recommendation result, a second recommendation result, and a third recommendation result. Distribution and integration on the first recommendation result, the second recommendation result, and the third recommendation result are performed according to weights to obtain recommended content to be recommended to the specified user. Search behavior data, browsing behavior data, and click behavior data on recommended content are taken into comprehensive consideration, data used in recommendation is enriched, and accuracy of recommendation is improved.

Abstract: This application relates to a target detection method performed at a computer device. The method includes: obtaining a to-be-detected image; extracting a first image feature and a second image feature corresponding to the to-be-detected image; performing dilated convolution to the second image feature, to obtain a third image feature corresponding to the to-be-detected image; performing classification and regression to the first image feature and the third image feature, to determine candidate position parameters corresponding to a target object in the to-be-detected image and degrees of confidence corresponding to the candidate position parameters; and selecting a valid position parameter from the candidate position parameters according to their corresponding degrees of confidence, and determining a position of the target object in the to-be-detected image according to the valid position parameter. The solutions in this application can improve robustness and consume less time.

Abstract: A metrics collection method includes: transmitting a media data obtaining request to an application service device in response to a trigger operation for streaming media; obtaining a media data response message transmitted by the application service device, the media data response message including metrics collection configuration information, and the metrics collection configuration information including metrics collection environment information and network slice information; obtaining environment information of the streaming media, and when the environment information matches the metrics collection environment information, collecting metrics data corresponding to the streaming media; determining, based on the network slice information, a network path for reporting the metrics data; and reporting the metrics data to the application service device through the network path.

Abstract: A recommendation method is provided. In the method, a candidate item to be recommended to a social network user is obtained. The social network user has at least two different types of social relationships. For at least one target social object in each of the at least two different types of social relationships of the social network user, attention of each of the at least one target social object in the respective type of social relationship to the candidate item is determined. According to the attention of each of the at least one target social object in the at least two different types of social relationships to the candidate item, a comprehensive attention of the target social objects of the at least two different types of social relationships to the candidate item is determined. According to the comprehensive attention, whether to recommend the candidate item to the social network user is determined.

Abstract: A computer device extracts a plurality of target windows from a target video. Each of the target windows comprises a respective plurality of consecutive video frames. For each of the target windows, the device performs action recognition on the respective plurality of consecutive video frames corresponding to the target window to obtain respective first action feature information of the target window. The device obtains a similarity between the first action feature information of the target window and preset feature information. The device determines, from the respective obtained similarities corresponding to the plurality of target windows, a highest first similarity and a first target window corresponding to the highest first similarity. The device also determines a dynamic action corresponding to the highest first similarity as the preset dynamic action in accordance with threshold settings.

Abstract: An application acceleration method includes identifying a data packet to be transmitted by an application running on a mobile terminal as a data packet to be accelerated to an application server, and determining network communication qualities of a first network transmission path to an access node via a wireless LAN communication network and a second network transmission path to the access node via a mobile network. The method further includes selecting a network transmission path based on network communication quality from the first network transmission path and the second network transmission path, and transmitting the data packet to the access node via the selected network transmission path such that the access node transmits the data packet to the application server through the network acceleration channel. Apparatus and non-transitory computer-readable storage medium counterpart embodiments are also contemplated.

Abstract: In an inter prediction encoding method, a picture is divided into a plurality of coding units. Motion estimation traversal is performed on motion vector predictions (MVPs) in a specified inter prediction mode to obtain candidate motion vectors. A motion vector set is determined from the MVPs and the candidate motion vectors. The motion vector set includes a target MVP from the MVPs and a target motion vector from the candidate motion vectors. Interpolation mode transversal and motion mode transversal are performed for each of the coding units based on the motion vector set to obtain a target interpolation mode and a target motion mode corresponding to the respective coding unit.

Abstract: This application disclose a method for training a model performed at a computing device. The method includes: acquiring a template image and a test image; invoking a first object recognition model to process a feature of a tracked object in the template image to obtain a first reference response, and a second object recognition model to process the feature in the template image to obtain a second reference response; invoking the first model to process a feature of a tracked object in the test image to obtain a first test response, and the second model to process the feature to obtain a second test response; tracking the first test response to obtain a tracking response of the tracked object; and updating the first object recognition model based on differences between the first and second reference responses, that between the first and second test responses, and that between a tracking label and the tracking response.

Abstract: A method by a network device for outputting a virtual application object includes acquiring current status information of a plurality of virtual application objects in a virtual application, the current status information indicating that a virtual application object is in a known state or in an unknown state, constructing a virtual application object status plane based on the current status information of the plurality of virtual application objects, where the virtual application object status plane includes a region corresponding to each virtual application object, the region includes the current status information of the corresponding virtual application object, determining, based on the virtual application object status plane, output probabilities corresponding to a plurality of to-be-outputted virtual application objects, and determining, based the output probabilities corresponding to the plurality of to-be-outputted virtual application objects, a target virtual application object from the plurality of t

Abstract: Aspects of the disclosure provide an image processing method, an image processing terminal, an image processing apparatus, and a non-transitory computer-readable storage medium. The method can include performing face detection on a target image to detect a face region in the target image. The method includes determining an expression class of the detected face region based on a trained expression recognition model and determining whether the determined expression class of the detected face region is a target expression class. If the determined expression class is the target expression class, head detection is performed to identify a head region in the target image and the identified head region is edited. If the determined expression class is not the target expression class, the head detection is not performed on the target image.

Abstract: This disclosure provides a method and a system for detecting and recognizing a target object in a real-time video. The method includes: determining whether a target object recognition result RX-1 of a previous frame of image of a current frame of image is the same as a target object recognition result RX-2 of a previous frame of image of the previous frame of image; performing target object position detection in the current frame of image by using a first-stage neural network to obtain a position range CX of a target object in the current frame of image when the two recognition results RX-1 and RX-2 are different; or determining a position range CX of a target object in the current frame of image according to a position range CX-1 of the target object in the previous frame of image when the two recognition results RX-1 and RX-2 are the same; and performing target object recognition in the current frame of image according to the position range CX by using a second-stage neural network.