Abstract: Provided are a navigation broadcast detection method and apparatus, an electronic device, and a medium. The navigation broadcast detection method includes acquiring navigation broadcast information associated with a simulated navigation route; and detecting the navigation broadcast information according to broadcast attribute information corresponding to the navigation broadcast information, where the broadcast attribute information includes broadcast time information and/or broadcast location information.

Abstract: Provided are a method and apparatus for testing an electronic map, an electronic device, and a storage medium. The method for testing an electronic map includes that N search words input by a user is acquired through the electronic map, where N is a natural number greater than or equal to 1; a correspondence between the N search words and policy scenarios is determined; a user scenario corresponding to each search word and a policy scenario corresponding to each search word are obtained based on a predetermined correspondence between the N search words and a user scenario and the correspondence between the N search words and the policy scenario; and the electronic map is tested based on a user scenario corresponding to each search word and the policy scenario corresponding to each search word.

Abstract: The present disclosure discloses a method and apparatus for training a model, a method and apparatus for synthesizing a speech, a device and a storage medium, and relates to the field of natural language processing and deep learning technology. The method for training a model may include: determining a phoneme feature and a prosodic word boundary feature of sample text data; inserting a pause character into the phoneme feature according to the prosodic word boundary feature to obtain a combined feature of the sample text data; and training an initial speech synthesis model according to the combined feature of the sample text data, to obtain a target speech synthesis model.

Abstract: The present disclosure provides a method and apparatus of synthesizing a speech, a method and apparatus of training a speech synthesis model, an electronic device, and a storage medium. The method of synthesizing a speech includes acquiring a style information of a speech to be synthesized, a tone information of the speech to be synthesized, and a content information of a text to be processed; generating an acoustic feature information of the text to be processed, by using a pre-trained speech synthesis model, based on the style information, the tone information, and the content information of the text to be processed; and synthesizing the speech for the text to be processed, based on the acoustic feature information of the text to be processed.

Abstract: The present disclosure provides a method for visual question answering, which relates to a field of computer vision and natural language processing. The method includes: acquiring an input image and an input question; constructing a Visual Graph based on the input image, wherein the Visual Graph comprises a Node Feature and an Edge Feature; updating the Node Feature by using the Node Feature and the Edge Feature to obtain an updated Visual Graph; determining a question feature based on the input question; fusing the updated Visual Graph and the question feature to obtain a fused feature; and generating a predicted answer for the input image and the input question based on the fused feature. The present disclosure further provides an apparatus for visual question answering, a computer device and a non-transitory computer-readable storage medium.

Abstract: Embodiments of the present disclosure provide a bend driving control method for an autonomous vehicle, a device and a storage medium, and relate to a field of perception and autonomous driving technologies. The method includes: obtaining an occupancy width of an autonomous vehicle on a target bend when the autonomous vehicle drives on the target bend; detecting location information of an obstacle on the target bend; and controlling a driving route of the autonomous vehicle on the target bend based on the occupancy width and the location information of the obstacle.

Abstract: A method, an apparatus, an electronic device and a computer readable storage medium for classifying a video are provided. The method may include: acquiring a to-be-classified video and an image complexity of the to-be-classified video; extracting a feature map with a resolution corresponding to the image complexity from the to-be-classified video; and determining a target video class to which the to-be-classified video belongs based on the feature map.

Abstract: A superconducting circuit structure, a superconducting quantum chip, and a superconducting quantum computer are provided, which are related to a field of quantum computing. The specific implementation includes: a superconducting circuit structure, including: at least three computational qubits; a bus qubit connected to the respective computational qubits, wherein couplings between two of the computational qubits connected by the bus qubit are equivalent; and coupler qubits disposed between the respective computational qubits and the bus qubit, to connect the respective computational qubits to the bus qubits, wherein the coupler qubit is configured to regulate coupling strength between the computational qubit and the bus qubit. Couplings between any two computational qubits may be realized, so that an operation of a quantum gate between any two computational qubits is achieved, while crosstalk between computational qubits may be effectively suppressed.

Abstract: Provided are a blockchain-based data verification method and apparatus, a device, and a storage medium, relating to the field of computer technology, for example, a blockchain technology, and applicable to cloud computing and cloud services. The solution includes acquiring a data verification transaction request initiated by a data owner; generating a response signature value in the current verification round according to the data verification transaction request; and sending the response signature value to a blockchain network. The response signature value is configured to instruct the blockchain network to verify whether the to-be-verified data block is stored in a data storer.

Abstract: There is provided a method for video processing, an electronic device, and a storage medium, which relates to the technical field of image processing, specifically to technical fields such as digital video and image display, which may be used in intelligent cloud and cloud computing scenarios. A specific implementation solution involves: acquiring ambient brightness data of a display device, the display device adopting a standard dynamic range (SDR) technology; obtaining screen brightness data of the display device according to video brightness data of to-be-displayed high dynamic range (HDR) video, metadata of the HDR video, and the ambient brightness data; wherein the video brightness data is obtained by tone mapping according to the metadata; and controlling, by using the screen brightness data, the display device to display the HDR video.

Abstract: A method and an apparatus for generating an offline map are disclosed. The method includes: obtaining 1st to nth environmental images sequentially collected by a camera of a vehicle when the vehicle is traveling on a target road section; selecting ith to jth environmental images from the 1st to Nth environmental images, performing a first batch of three-dimensional modeling on the ith to jth environmental images to obtain first posture information of the camera and a first world coordinate; performing a second batch of three-dimensional modeling in parallel on the 1st to (i?1)th environmental images and (j+1)th to Nth environmental images, based on the first posture information and the first world coordinate, to obtain a second world coordinate and to obtain a third world coordinate; and generating an offline map of the target road section according to the world coordinate.

Abstract: The present disclosure discloses a method and apparatus for scheduling a resource for a deep learning framework. The method can comprise: querying statuses of all deep learning job objects from a Kubernetes platform at a predetermined interval; and submitting, in response to finding from the queried deep learning job objects a deep learning job object having a status conforming to a resource request submission status, a resource request to the Kubernetes platform to schedule a physical machine where the Kubernetes platform is located to initiate a deep learning training task. The method can completely automate the allocation and release on the resource of the deep learning training task.

Abstract: A method for detecting a surface defect, a method for training model, an apparatus, a device, and a medium, are provided. The method includes: inputting a surface image of the article for detection into a defect detection model to perform a defect detection, and acquiring a defect detection result output by the defect detection model; inputting a surface image of a defective article determined to be defective into an image discrimination model based on the defect detection result to determine whether the surface image of the defective article is defective, wherein the image discrimination model is a trained generative adversarial networks model, and the generative adversarial networks model is obtained by training using a surface image of a defect-free good article; and adjusting the defect detection result of the surface image of the defective article according to a determination result of the image discrimination model.

Abstract: A method of generating a virtual idol is provided. The method includes: during obtaining of a virtual idol, feature information of a target object may be obtained, and then the feature information of the target object is used as a generation basis for the virtual idol, so that a target virtual face matching with the feature information may be determined from a preset face material library in a targeted manner, and a target motion video matching with the feature information may be determined from a preset motion video library; and then the virtual face and a facial image in the motion video are fused, which may generate the virtual idol for a scenario where the target object is endorsed, so that the virtual idol may subsequently be used to endorse the target object.

Abstract: Provided are a joint perception model training method, a joint perception method, a device, and a storage medium. The joint perception model training method includes: acquiring sample images and perception tags of the sample images; acquiring a preset joint perception model, where the joint perception model includes a feature extraction network and a joint perception network; performing feature extraction on the sample images through the feature extraction network to obtain target sample features; performing joint perception through the joint perception network according to the target sample features to obtain perception prediction results; and training the preset joint perception model according to the perception prediction results and the perception tags, where the joint perception includes executing at least two perception tasks.

Abstract: An electronic map update method includes: determining an update period of a first electronic map corresponding to a user equipment in response to a map update request sent by the user equipment; determining at least one piece of per-period incremental information currently corresponding to a second electronic map of a latest version; where the per-period incremental information includes an incremental period, the per-period incremental information is a data change record of an electronic map in the incremental period, and the incremental period is a period for starting an incremental conversion of the electronic map; querying, from the at least one piece of per-period incremental information, target incremental information of which a corresponding incremental period is located in the update period; and updating the first electronic map of the user equipment to the second electronic map based on the target incremental information.

Abstract: Technical solutions relate to the fields of artificial intelligence technologies and voice technologies. A technical solution includes: performing voice recognition and demand analysis on a voice instruction input by a user; in response to an unknown demand obtained by the demand analysis, acquiring information of a query entity and query content using a result of the demand analysis, and acquiring reply information corresponding to the query content by communication with the query entity; and returning a first voice response to the user using the reply information.

Abstract: Provided are a blockchain-based data verification method and apparatus, a device, and a storage medium, relating to the field of computer technology, for example, a blockchain technology, and applicable to cloud computing and cloud services. The solution includes acquiring a data verification transaction request initiated by a data owner; generating a response signature value in the current verification round according to the data verification transaction request; and sending the response signature value to a blockchain network. The response signature value is configured to instruct the blockchain network to verify whether the to-be-verified data block is stored in a data storer.

Abstract: The present disclosure discloses a data mining method, a data mining apparatus, an electronic device and a storage medium, relates to the technical field of the Internet, and in particular to the Internet big data processing technology. The method includes: acquiring a current article to be mined; obtaining information values required for each data identification strategy of multiple data identification strategies from the current article, and each data identification strategy is used for identifying a preset type of data; identifying a data type of the current article according to the information values required for each data identification strategy to obtain a data type identification result; and determining whether the current article belongs to any preset type of data according to the data type identification result.

Abstract: Provided by the present disclosure is a new category tag mining method, involving the field of knowledge graph technology, and including: obtaining a plurality of queries during a current preset time period; labeling a category tag on each query of the plurality of queries, by using a pre-trained sequence labeling model, to extract the category tag currently corresponding to the query from the query; and removing a category tag already existing in a preset current category tag library from category tags currently corresponding to all the queries, and determining a remaining category tag as a new category tag. The present disclosure also provides an electronic device and a non-transitory computer-readable storage medium.