Abstract: There is provided a method for cross-regional talent flow intention analysis, an electronic device, and a storage medium, which relates to technical fields such as big data processing and data statistics and analysis. A specific implementation solution involves: constructing a talent flow intention network based on search data in a network within a preset period of time; and performing cross-regional talent flow intention analysis based on the talent flow intention network to obtain a talent flow intention analysis result.

Abstract: A camera extrinsic parameter correction method includes acquiring multiple road surface images continuous in time and performing classification to obtain a mutated image and a time-adjacent image corresponding to the mutated image; determining a matching point pair from pixel points of the mutated image and pixel points of the corresponding time-adjacent image and determining a target view angle point pair of the matching point pair in a target view angle; and correcting a camera extrinsic parameter corresponding to the mutated image according to the difference between two target view angle points in the target view angle point pair, where the camera extrinsic parameter is configured for conversion of a pixel point in a current view angle into a pixel point in the target view angle.

Abstract: Embodiments of the present application disclose a vehicle positioning method, an apparatus, an electronic device, a vehicle and a storage medium, and relate to the field of automatic driving technology. A specific implementation includes: obtaining perceptual information of a lane where a vehicle is located, and obtaining high-precision information of the lane from a preset high-precision map, where the perceptual information and the high-precision information both include lane line information, and both include curb information and/or guardrail information; determining matching information of the perceptual information and the high-precision information; generating position information of the vehicle according to the matching information.

Abstract: The present disclosure provides a generalization processing method, apparatus, device and computer storage medium, and relates to technical field of artificial intelligence and specifically to a deep learning technique. A specific implementation solution is: determining a set of candidate queries in a query library that are similar to a requested query in at least one of a literal matching manner, a semantic matching manner and a query rewriting manner; determining a generalized query corresponding to the requested query from the set of candidate queries by using a pre-trained query matching model; wherein the query matching model is obtained by pre-training based on a cross attention model. The generalization for the requested query can be achieved according to the present disclosure.

Abstract: The present disclosure provides a landform map building method and apparatus, an electronic device and a readable storage medium, and relates to the field of image processing technologies.

Abstract: A video generation method is provided. The video generation method includes: obtaining global semantic information and local semantic information of a text, where the local semantic information corresponds to a text fragment in the text, searching, based on the global semantic information, a database to obtain at least one first data corresponding to the global semantic information; searching, based on the local semantic information, the database to obtain at least one second data corresponding to the local semantic information; obtaining, based on the at least one first data and the at least one second data, a candidate data set; matching, based on a relevancy between each of at least one text fragment and corresponding candidate data in the candidate data set, target data for the at least one text fragment; and generating, based on the target data matched with each of the at least one text fragment, a video.

Abstract: A method for generating a relighted image includes: obtaining a to-be-processed image and a guidance image corresponding to the to-be-processed image; obtaining a first intermediate image consistent with an illumination condition in the guidance image by performing relighting rendering on the to-be-processed image in a time domain based on the guidance image; obtaining a second intermediate image consistent with the illumination condition in the guidance image by performing relighting rendering on the to-be-processed image in a frequency domain based on the guidance image; and obtaining a target relighted image corresponding to the to-be-processed image based on the first intermediate image and the second intermediate image.

Abstract: The present disclosure provides a signal processing method and apparatus, a device, and a storage medium. The method includes: acquiring a signal set to be processed that carries base station information and base station access time; determining a first signal subset that further carries position information in the signal set to be processed; determining position information of a base station of a first type deployed in a subway station according to the base station information and the position information that are carried by the signal of the first signal subset; and determining position information of a base station of a second type deployed in a subway tunnel according to the position information of the base station of the first type, and the base station information and base station access time that are carried by the signal of the signal set to be processed.

Abstract: A method and an apparatus for measuring temperature, and a computer-readable storage medium includes detecting a target position of an object in an input image; determining key points of the target position and weight information of each key point based on a detection result of the target position, in which the weight information is configured to indicate a probability of each key point being covered; acquiring temperature information of each key point; and determining a temperature of the target position at least based on the temperature information and the weight information of each key point.

Abstract: The present disclosure provides a character recognition model training method and apparatus, a character recognition method and apparatus, a device and a medium, relating to the technical field of artificial intelligence, and specifically to the technical fields of deep learning, image processing and computer vision, which can be applied to scenarios such as character detection and recognition technology. The specific implementing solution is: partitioning an untagged training sample into at least two sub-sample images; dividing the at least two sub-sample images into a first training set and a second training set; where the first training set includes a first sub-sample image with a visible attribute, and the second training set includes a second sub-sample image with an invisible attribute; performing self-supervised training on a to-be-trained encoder by taking the second training set as a tag of the first training set, to obtain a target encoder.

Abstract: A method for displaying annotation information, an electronic device and a storage medium, related to the field of computers and image information processing, are provided. The method includes: acquiring depth information and annotation information of a target region in a first image at a first angle of view; establishing an association relationship between the depth information and the annotation information; and in a case that a second image at a second angle of view is acquired, determining a display region of the target region in the second image based on the depth information, and displaying, in the display region in the second image, the annotation information of the target region based on the association relationship. Thereby, the cross-image display of the annotation information of the target region with the depth information can be realized.

Abstract: The present application discloses a vehicle re-identification method and apparatus, a device and a storage medium, which relates to the field of computer vision, intelligent search, deep learning and intelligent transportation. The specific implementation scheme is: receiving a re-identification request from a terminal device, the re-identification request including a first image of a first vehicle shot by a first camera and information of the first camera; acquiring a first feature of the first vehicle and a first head orientation of the first vehicle according to the first image; determining a second image of the first vehicle from images of multiple vehicles according to the first feature, multiple second features extracted based on the images of the multiple vehicles in an image database, the first head orientation of the first vehicle, and the information of the first camera; and transmitting the second image to the terminal device.

Abstract: A method for distributing network layers in a neural network model includes: acquiring a to-be-processed neural network model and a computing device set; generating a target number of distribution schemes according to network layers in the to-be-processed neural network model and computing devices in the computing device set, the distribution schemes including corresponding relationships between the network layers and the computing devices; according to device types of the computing devices, combining the network layers corresponding to the same device type in each distribution scheme into one stage, to obtain a combination result of each distribution scheme; obtaining an adaptive value of each distribution scheme according to the combination result of each distribution scheme; and determining a target distribution scheme from the distribution schemes according to respective adaptive value, and taking the target distribution scheme as a distribution result of the network layers in the to-be-processed neural n

Abstract: A technical solution relates to distributed machine learning, and relates to the field of artificial intelligence technologies, such as machine learning technologies, or the like. An implementation includes: acquiring, based on delay information, an optimal scheduling queue of a plurality of edge devices participating in training; and scheduling each edge device of the plurality of edge devices to train a machine learning model based on the optimal scheduling queue of the plurality of edge devices.

Abstract: A mapping method, an electronic device and a readable storage medium, which relate to the fields of map generation technologies, indoor localization technologies, are disclosed. The mapping method includes: acquiring current frame point cloud data of a target scenario to obtain a submap sequence and an active submap corresponding to the current frame point cloud data; acquiring initial posture data of the current frame point cloud data, and obtaining target posture data of the current frame point cloud data according to the initial posture data and the active submap; obtaining at least one posture constraint condition according to the target posture data of the current frame point cloud data and the submap sequence; and performing posture optimization on the submap sequence according to the at least one posture constraint condition, and obtaining a mapping result of the target scenario according to the submap sequence after the posture optimization.

Abstract: A method is provided which includes: obtaining a set of sequence lengths for performing randomized benchmarking on the quantum computer; performing, for each m, the following operations R times: obtaining m quantum gates that are randomly generated, and quantum gates corresponding to respective inverse operations of the m quantum gates; constructing a quantum circuit, wherein the m quantum gates are sequentially connected in a first order, and the quantum gates corresponding to the respective inverse operations of the m quantum gates are sequentially connected behind the m quantum gates in an order opposite the first order; applying an initial quantum state to the quantum circuit to perform a plurality of standard basis measurements; and determining a number of occurrences of an all-zero sequence; fitting an objective function based on an average expected value corresponding to each m obtained after R operations; and determining an average precision of the quantum computer.

Abstract: The present disclosure provides a vision processing and model training method, device, storage medium and program product. A specific implementation solution is as follows: establishing an image classification network with the same backbone network as the vision model, performing a self-monitoring training on the image classification network by using an unlabeled first data set; initializing a weight of a backbone network of the vision model according to a weight of a backbone network of the trained image classification network to obtain a pre-training model, the structure of the pre-training model being consistent with that of the vision model, and optimize the weight of the backbone network by using real data set in a current computer vision task scenario, so as to be more suitable for the current computer vision task; then, training the pre-training model by using a labeled second data set to obtain a trained vision model.

Abstract: A method of processing map data, an electronic device, and a storage medium, which relate to a field of a computer technology, in particular to fields of intelligent transportation technology, image processing technology, etc. The method of processing the map data includes: processing sensor data for a traffic object to obtain point cloud data for the traffic object, where the sensor data includes image data; obtaining mesh data based on the point cloud data; processing the image data based on an association between the mesh data and the image data, so as to obtain processed image data; and obtaining the map data for the traffic object based on the processed image data.

Abstract: Disclosed are a method, apparatus and electronic device for annotating information of a structured document. A specific implementation is: obtaining a template image of a structured document and at least one piece of annotation information of a field to be filled in the template image, where the annotation information includes attribute value and historical content of the field to be filled, and historical position of the field to be filled in the template image; generating, according to the attribute value of the field to be filled, the historical content of the field to be filled and the historical position of the field to be filled in the template image, target filling information of the field to be filled; obtaining, according to the target filling information of the field to be filled, an image of an annotated structured document.

Abstract: A data processing method is provided. The method includes: obtaining a sample data set for modeling; selecting a first sample data from the sample data set; generating, in response to determining that a similarity between a first semantic vector corresponding to a first feature dimension and a second semantic vector corresponding, to a second feature dimension meets a preset condition, a second sample data based on the first sample data; and adding the second sample data to the sample data set.