Abstract: The present disclosure provides a target detection and model training method and apparatus, a device and a storage medium, and relates to the field of artificial intelligence, and in particular, to computer vision and deep learning technologies, which may be applied to smart city and intelligent transportation scenarios. The target detection method includes: performing feature extraction processing on an image to obtain image features of a plurality of stages of the image; performing position coding processing on the image to obtain a position code of the image; obtaining detection results of the plurality of stages of a target in the image based on the image features of the plurality of stages and the position code; and obtaining a target detection result based on the detection results of the plurality of stages.

Abstract: Provided are a method and apparatus for updating an edge node, a device, a medium and a program product which relate to the technical field of computers and in particular to the technical fields of edge computing, cloud computing and cloud services. In an embodiment, a module update instruction is received from a cloud server, where the module update instruction includes information about a to-be-updated module; an auxiliary unit or a master unit is used as a target module according to the information about the to-be-updated module, and the to-be-updated module is updated through the target module; and in a process of updating the to-be-updated module, data interaction is performed between the target module and the cloud server.

Abstract: The present disclosure discloses a control method and a control apparatus for speech interaction. The detailed implementation solution of the control method for the speech interaction includes: collecting an audio signal; detecting a wake-up word in the audio signal to obtain a wake-up word result; and playing a prompt tone and/or executing a speech instruction in the audio signal based on the wake-up word result.

Abstract: Provided are a tour guiding method and apparatus, an electronic device and a storage medium. The method includes receiving a video stream collected by a user in a current location area of a target scenic spot and sent by an application device; determining, based on the collected video stream and prestored three-dimensional point cloud data of the target scenic spot, an augmented-reality-based content resource package corresponding to the current location area, where the augmented-reality-based content resource package includes at least six-degrees-of-freedom attitude data of the application device; and sending the augmented-reality-based content resource package corresponding to the current location area to the application device to enable the application device to provide the augmented-reality-based content resource package corresponding to the front location area for the user.

Abstract: Provided are a method and an apparatus for processing audio, an electronic device and a storage medium. A specific implementation solution includes: obtaining a first target feature vector from original audio, where the first target feature vector is used for representing a phoneme feature of the original audio; obtaining a second target feature vector and a third target feature vector from audio to be transferred, where the second target feature vector is used for representing a style prosody feature of the audio to be transferred, and the third target feature vector is used for representing a speaker feature of the audio to be transferred; performing spectrogram decoding on the first target feature vector, the second target feature vector and the third target feature vector to obtain a target spectrogram feature; and converting the target spectrogram feature into target audio.

Abstract: The disclosure provides a method and an apparatus for generating a response, an electronic device, and a storage medium. The method includes: obtaining a current user request in a current conversation and historical coreference information in the current conversation; extracting content matching the current user request from the historical coreference information; updating the current user request based on the content to obtain an updated current user request; and generating a response of the current user request based on the updated current user request.

Abstract: A method and apparatus for storing autonomous driving test data and an electronic device are provided. The method may include: acquiring a task type of a test task of an autonomous vehicle; receiving message data acquired in a test of the autonomous vehicle and corresponding to the task type, and writing the message data into a data queue; creating a log file corresponding to the task type, writing the message data corresponding to the task type in the data queue into the log file, and transferring the log file and a file name of the log file to the data queue; acquiring preset disk drop scenario information corresponding to the task type; and adding, according to the preset disk drop scenario information, an unclearable mark to the log file in the data queue having data acquisition time consistent with the time of triggering disk drop storage of data.

Abstract: A method and apparatus for promoting a motion, an electronic device and a storage medium, relating to the field of image recognition technology are provided. An embodiment of the method may include: acquiring a user motion image, and acquiring three-dimensional recognition coordinates of body key points recognized in the user motion image; determining, based on the three-dimensional recognition coordinates, a user motion matching the user motion image; screening, according to a mapping relationship between user motion and body key points, a target body key point among all of the recognized body key points; acquiring three-dimensional standard coordinates of the target body key point corresponding to the user motion; and prompting a motion based on values of differences between the three-dimensional standard coordinates of the target body key point and the three-dimensional recognition coordinates of the target body key point.

Abstract: A method of generating a font database, and a method of training a neural network model are provided, which relate to a field of artificial intelligence, in particular to a computer vision and deep learning technology. The method of generating the font database includes: determining, by using a trained similarity comparison model, a basic font database most similar to handwriting font data of a target user in a plurality of basic font databases as a candidate font database; and adjusting, by using a trained basic font database model for generating the candidate font database, the handwriting font data of the target user, so as to obtain a target font database for the target user.

Abstract: Provided are a video recognition method and apparatus, an electronic device, a medium and a computer program product. The video recognition method is described below. A to-be-recognized video is divided into at least two video segments; video frames are extracted from the at least two video segments, and feature recognition is performed on the video frames to obtain initial semantic feature blocks of the at least two video segments; each of the initial semantic feature blocks is fused, and a fused target semantic feature block is obtained; and a type of the to-be-recognized video is determined according to the fused target semantic feature block.

Abstract: The human body 3D key point detection method includes: acquiring a to-be-detected image, the to-be-detected image including first human body image data; inputting the to-be-detected image into a key point extraction model to acquire N first 3D heatmaps of N human body 3D key points in the first human body image data, each first 3D heatmap representing a Gaussian distribution of one human body 3D key point in first human body image data in a predetermined space, where N is a positive integer; and determining coordinate information about the N human body 3D key points in the first human body image data based on the N first 3D heatmaps.

Abstract: Provided are a method and apparatus for applet page rendering, an electronic device and a storage medium. The method for applet page rendering includes steps described below. Original incremental rendering is performed on an applet page based on a pre-obtained first drawing result of the applet page to obtain an original incremental rendering result of the applet page. Rendering is performed on the applet page based on the pre-obtained first drawing result of the applet page, the original incremental rendering result of the applet page and a pre-obtained initial incremental rendering result of the applet page.

Abstract: Provided are a real-time prediction method, an electronic device and a non-transitory computer-readable storage medium, which relate to the field of data processing, and in particular to the field of artificial intelligence. The specific implementation solution is acquiring a user request based on a business scenario; acquiring, from a plurality of pre-stored original features, at least one target original feature corresponding to the user identifier; determining, from a plurality of pre-trained models, a target model corresponding to the scenario identifier, and determining, from a plurality of feature engineering services, a target feature engineering service corresponding to the target model; performing real-time feature processing on the at least one target original feature by means of the target feature engineering service, so as to obtain a target model entry feature; and inputting the target model entry feature into the target model.

Abstract: Embodiments of the disclosure disclose a method for a vehicle avoiding an obstacle, an electronic device, and a computer storage medium, and relates to a field of unmanned driving technologies. The detailed implementation includes: obtaining size information of a vehicle; obtaining a safe distance in a traveling direction of the vehicle; determining an obstacle screening area of the vehicle at least based on the size information and the safe distance; and determining an obstacle avoiding path of the vehicle in response to determining that the obstacle is located in the obstacle screening area. With the technical solution of the disclosure, higher efficiency obstacle avoiding can be realized.

Abstract: The present application discloses a method and an apparatus for recognizing text content, and an electronic device, and relates to a text recognition technique in the field of computer technology. The specific implementation is as follows: acquiring a dial picture; detecting at least one text centerline and a bounding box corresponding to each text centerline in the dial picture; and recognizing text content in each line of text in the dial picture based on the at least one text centerline and the bounding box corresponding to each text centerline.

Abstract: The satellite image processing method includes: acquiring a first target satellite image; defogging the first target satellite image through a first neural network to acquire a first satellite image; and adjusting an image quality parameter of the first satellite image through a second neural network to acquire a second satellite image.

Abstract: A method for pushing information, and an electronic device are disclosed. The method includes: obtaining a plurality of initial pages containing document content; predicting, based on the document content in the plurality of initial pages, an effective rate for pushing information using each initial page; selecting, based on the effective rate, at least one candidate page from the plurality of initial pages and extracting a first keyword from the document content of the at least one candidate page; and determining a target page for mounting information to be pushed from the at least one candidate page, based on a matching degree between a second keyword of the information to be pushed and the first keyword.

Abstract: Provided are an image detection method and apparatus, a device, a storage medium and a computer program product, the method includes: performing feature extraction on an image to be detected to obtain a feature map; performing target detection on the feature map through a target branch network to obtain target detection information of candidate anchor boxes at a pixel position of the feature map; performing keypoint detection on the feature map through a keypoint branch network to obtain positions of keypoints in the candidate anchor boxes at the pixel position of the feature map, and generating heatmap groups of the candidate anchor boxes according to the positions of the keypoints; and obtaining information about a target object in the image to be detected and positions of keypoints of the target object according to the target detection information and the heatmap groups.

Abstract: The present disclosure provides techniques for recommending objects. The techniques can include: recognizing a retrieval image including a retrieval object from a target user. A retrieval feature can be obtained from the retrieval object, and at least one retrieval feature image can be obtained from a first database based on the retrieval feature. The retrieval image can include a plurality of feature images, and a target object image set can be obtained from a second database based on the at least one retrieval feature image. The target image set includes a plurality of object images to be recommended to the target user.

Abstract: A cross-regional travel recommendation method and apparatus, an electronic device and a storage medium are provided, which relates to the fields of intelligent transportation and deep learning. A specific implementation solution is: acquiring a travel request of a user, the travel request comprising a start point and an end point which are located in different regions; extracting user features according to the travel request of the user; and recommending at least one travel plan to the user according to the user features and a pre-trained cross-regional travel recommendation model. The technical solutions can make up for the deficiency of the existing technology, provide a cross-regional travel plan recommendation under a large-space scale and a multimodal environment through a pre-trained cross-regional travel recommendation model and user features extracted based on a travel request of a user, and can satisfy a cross-regional travel request of the user, and is highly practical.