55 results about "Viewdata" patented technology

The invention discloses a power data communication network security situation prediction method, which comprises the following steps of: aiming at a hot spot multi-dimensional orientation description vector, acquiring a network security event log, adopting a time sequence event chain construction technology, and determining event triggering frequency and service interruption duration related to a hot spot through matching of event triggering frequency and event association strength, so as to predict the security situation of the hot spot. Obtaining an event chain sequence; extracting an event trigger frequency, a service interruption duration and a hotspot influence range from the event chain sequence, and judging a hotspot life cycle stage through quantification of a node load state and traffic abnormal fluctuation to obtain a life cycle quantitative index; and extracting a hot spot influence range and traffic abnormal fluctuation from the global security situation view data, and if the hot spot influence range or the traffic abnormal fluctuation exceeds a preset threshold, adjusting weight redistribution through a node load state to obtain an incremental change feature set. According to the method, the hotspot situation in the power data communication network can be comprehensively and dynamically analyzed, and powerful support is provided for network security management and decision making.

The invention discloses a motor imagery electroencephalogram decoding method based on multi-view space-time convolution and an attention mechanism, which comprises the following steps of: firstly, constructing multi-view data by utilizing a filter bank, and enhancing training data by adopting a frequency band sensing fragment splicing strategy so as to expand sample distribution; secondly, respectively and accurately capturing specific time sequence features and spatial features of different frequency bands through a frequency adaptive convolution kernel and depth separable convolution; meanwhile, in combination with a channel attention mechanism and a time sequence statistics module, feature channel weights are effectively utilized, and a mean value and a logarithmic variance in a time window are calculated, so that the modeling capability of the model for key spatio-temporal information is enhanced. According to the method, the problem of insufficient spatio-temporal feature mining in the motor imagery task is effectively solved, and a competitive result is obtained.

A data transferring method comprises monitoring (210, fig 2) the contents of a data buffer 110, 120, determining (220, fig 2) that the contents contains sensitive data, obfuscating (230, fig 2) the se

This invention discloses a UAV detection method based on multi-view feature fusion using residual networks, comprising: constructing multi-view data: obtaining the time-domain plot, short-time Fourier transform plot, continuous wavelet transform plot, and Wegener-Will distribution plot of the measured signal; constructing a ResNet34, including an input structure, an intermediate structure, and an output structure; the input structure processes the input data through convolution and max pooling operations; the intermediate structure consists of four similar structural layers, each consisting of multiple residual blocks, each residual block containing three convolutional layers and a shortcut connection; starting from the second structural layer, the initial residual block of each structural layer also contains an up-dimensional sampling structure; constructing a multi-view feature fusion network model based on residual networks, and outputting the UAV detection accuracy after multi-view feature fusion at the output end. This invention improves the UAV detection efficiency by fusing features from the multi-view data of the signal.

The invention discloses a fusion representation method for incomplete multi-view data, and belongs to the technical field of information technology service. The method comprises the following steps: aiming at the problem that a traditional multi-view learning method cannot be suitable for incomplete multi-view data learning when views are missing, constructing a multi-view representation matrix aiming at an incomplete multi-view data set; optimizing a single view representation matrix; a single-view reconstruction learning model is constructed, and complementation of a missing view representation matrix is realized; constructing a target function by using the fusion representation model; the fusion representation model is trained, an optimal fusion representation matrix is obtained through model optimization, and the fusion representation matrix can be directly used as input of downstream tasks. According to the method, the key technology of fusion expression of multi-source heterogeneous multi-view data is broken through, the purposes of making full use of multiple views and reducing influences of incomplete views are achieved, and then downstream tasks in a network can be supported.

To provide a method and a device for encoding multi-view data for immersive video, a method and a device for decoding multi-view data, and a corresponding bit stream including metadata.SOLUTION: A method of encoding multiview data for immersive video includes generating metadata including a field indicating whether a patch data unit of the multiview data includes in-painted data. This metadata provides a way to distinguish between patch data units containing original texture and depth data and patch data units containing in-painted data (in-painted texture and depth data). Providing such information in the metadata of an immersive video addresses issues related to blending and pruned view reconstruction.SELECTED DRAWING: Figure 1

The application discloses a small sample robust modulation recognition method based on asymmetric double-view enhancement and AD-HCL loss, and belongs to the technical field of automatic modulation recognition of wireless communication signals. The method solves the problems that the prior art is strongly dependent on large-scale labeled data, is insufficient in robustness in a complex electromagnetic environment, and does not fully utilize unlabeled data. Technical scheme points include: a deep neural network fusing a convolution residual network, a bidirectional long short-term memory network and an attention mechanism is constructed for feature extraction; the network is unsupervised pre-trained by using asymmetric double-view data enhancement and an AD-HCL loss function; and the network is supervised fine-tuned by removing a projection head and connecting a new classifier and using a small amount of labeled data. The application can effectively utilize unlabeled data and realize high-precision and robust modulation recognition under a small sample condition.

The invention provides a method, device and equipment for modifying BIM link model data and a storage medium, and relates to the technical field of BIM design, and the method is applied to a BIM link scene and comprises the steps that an axis net of a BIM link model is loaded in a current document, when the axis net is in a model state, execution of editing operation on the axis net is forbidden, and in a current view, editing operation on the axis net is forbidden. And in response to a first state switching operation for the axis net in the current view, switching the axis net from a model state to a view state, and when the axis net is in the view state, in response to an editing operation for the axis net, modifying the axis net view data corresponding to the current view in the second data area without changing the axis net model data in the first data area. The invention provides the method. In a BIM model link scene, on the premise of not changing basic data of an axis network in a link document, flexible display and controlled editing of the axis network of the link model in a specific view of the current document are realized.

The application provides a processing method and device of video data based on left and right views, equipment and medium, the method comprises: determining left view data and right view data of a to-be-processed video; wherein the left view data is an image frame of a left eye view, and the right view data is an image frame of a right eye view; determining a parallax fusion feature of the to-be-processed video according to the left view data and the right view data; wherein the parallax fusion feature represents a left eye view and a left eye parallax map; determining a quality score of the to-be-processed video according to the parallax fusion feature and a preset text description; wherein the preset text description represents an evaluation dimension of the to-be-processed video, and the quality score represents a video quality of the to-be-processed video. The method of the application determines the parallax fusion feature of the to-be-processed video through the left view data and the right view data, and the parallax fusion feature of the to-be-processed video can improve the accuracy of data processing.

Methods and apparatus are disclosed herein to synthesize six degree-of-freedom views from sparce RGB-depth inputs. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to reproject a first red-green-blue (RGB) depth view and a second RGB depth view to a target camera position to obtain a first reprojected view and a second reprojected view, combine the first reprojected view and the second reprojected view into a blended view data based on a first weight map and a second weight map, the blended view including missing RGB depth information due to at least one of an occlusion or a disocclusion, and generate a six degree-of-freedom synthesized view of the blended view data, the synthesized view including the missing RGB depth information.

The invention discloses an electric energy substitution potential customer type identification method and device, a terminal and a medium, and the method comprises the steps: obtaining multi-dimensional original data from different data sources, converting the multi-dimensional original data into corresponding view data, screening out a representative anchor point in each view, calculating the similarity between each sample point and the anchor point, and carrying out the recognition of the type of a customer with the electric energy substitution potential. And constructing an initial similarity matrix of each view. And inputting the multi-view similarity matrix into a feature selection model, and gradually eliminating the noise influence of the low-weight views through model optimization. According to the scheme, firstly, the calculation complexity is reduced through anchor point screening, meanwhile, the view contribution degree is dynamically adjusted through the feature selection model, irrelevant feature interference is effectively restrained, multi-dimensional information such as power loads and equipment states can be integrated, and the method and the device have the advantages that the method and the device are easy to implement. The customer energy utilization potential under different environment conditions can be accurately identified, and the classification accuracy is improved.

The invention provides a remote 3D image data transmission and display method and device based on the Internet, and belongs to the technical field of 3D image data transmission. Environment images are collected by using a binocular fisheye camera synchronously configured at a robot end, are spliced into a single panoramic image after being cut, and are subjected to single-stream coding; an RTP protocol is adopted as a carrier and is transmitted to a client in combination with a differentiated reliability strategy of data classification, so that low delay and synchronism of the data are ensured; double-view data capable of being displayed are generated through single-time rendering processing, and the method is suitable for various 3D image display devices. Therefore, the traditional double-path flow is replaced by the single-flow coding, and the network congestion is effectively relieved; binocular images are spliced into a single-frame panoramic image at a robot end, and subsequent coding, transmission, decoding and rendering full links are all based on the same frame of data, so that the problem of frame desynchrony caused by delay jitter in traditional double-path transmission is solved, the teleoperation accuracy is improved, and meanwhile, the resource overhead of a client is greatly reduced.

The invention provides a multifunctional stomatology department lamp and a using method thereof.The multifunctional stomatology department lamp comprises a supporting frame, an illuminating lamp, a camera, a loudspeaker, an information transmission module, a control module and a power module, and the supporting frame is used for being fixed to the head; the illuminating lamp is fixed on the supporting frame, the camera is used for collecting view information and is also fixed on the supporting frame, the loudspeaker is located in the supporting frame, the information transmission module is wirelessly connected with external computer equipment, and the illuminating lamp, the loudspeaker, the camera and the information transmission module are all electrically connected with the control module. The power supply module is electrically connected with the control module; the shooting range of the camera adapts to the irradiation range of the illuminating lamp; the camera collects view data and transmits the view data to external computer equipment, guidance information is obtained through analysis, and the guidance information is transmitted to the loudspeaker; the lamp is good in lighting effect and further facilitates guidance and learning of the stomatology department doctors.

The present technology relates to a communication management system, a communication management method, a movable object, and a management apparatus that allow efficient transmission of three-dimensional configuration view data from a movable object. A plan generating unit that generates, on the basis of a state of a transmission channel on a movement route of a movable object and a priority of three-dimensional configuration view data to be used for generating a three-dimensional configuration view, a plan of a transmission timing that is a spatial timing at which the movable object transmits the three-dimensional configuration view data on the transmission channel. The present technology can be applied to, for example, a communication management system that updates the three-dimensional configuration view by using the three-dimensional configuration view data transmitted from the movable object.

The invention discloses a small sample robust modulation identification method based on asymmetric double view enhancement and AD-HCL loss, and belongs to the technical field of wireless communication signal automatic modulation identification. The problems that in the prior art, dependence on large-scale labeled data is high, robustness is insufficient in a complex electromagnetic environment, and unlabeled data is not fully utilized are solved. According to the technical scheme, the method comprises the following steps: constructing a deep neural network fusing a convolutional residual network, a bidirectional long-short-term memory network and an attention mechanism for feature extraction; carrying out unsupervised pre-training on the network by adopting asymmetric double-view data enhancement and an AD-HCL loss function; by removing a projection head and connecting a new classifier, supervised fine tuning is performed by using a small amount of marked data. According to the method, label-free data can be effectively utilized, and high-precision and robust modulation identification is realized under a small sample condition.

The application relates to an application feature data processing method and device, equipment and medium. The method comprises the following steps: acquiring stream feature data and / or batch feature data corresponding to feature data, performing data preprocessing on the stream feature data and / or batch feature data to determine a plurality of different feature data sets; extracting a feature subset corresponding to each application program from the plurality of feature data sets according to a preset rule, splicing the feature subset corresponding to each application program to determine a feature data set list corresponding to each application program, and sending the feature data set list to a program feature pool; acquiring feature view configuration information corresponding to each application program, determining view data corresponding to each application program from the feature data set list in the program feature pool according to the feature view configuration information; and pushing the view data to a target application program to display a feature view corresponding to each application program. The application can improve the flexibility, reusability and maintainability of feature data.

The invention discloses a base station evaluation method and a computer program product, and relates to the technical field of wireless. The base station evaluation method comprises the following steps: processing obtained multi-dimensional index data of a base station to obtain a multi-view data matrix; on the basis of the multi-view data matrix, a public view map is constructed, and the public view map is used for representing the weight of each view; clustering processing is carried out on the public view map to obtain a clustering result of the base station, and the clustering result is the category of the base station in a preset number of clustering clusters; and based on the clustering result and the weight of each view in the base station, evaluating the base station to obtain the grade of the base station.

The embodiment of the invention provides a data display method, device and equipment, a readable storage medium and a program product, and can be applied to fields or scenes such as artificial intelligence and application programs, the method comprises the steps that a data acquisition request is sent to a server, and the data acquisition request carries a data display position identifier of the application program; receiving data content and a first data style template determined by the server according to the data display position identifier, and analyzing the first data style template to obtain an analysis result; if the analysis result indicates that the analysis of the first data style template fails, determining a target view object meeting an object selection requirement from candidate view objects stored in a local storage space; and generating first view data according to the data content and the target view object, and performing display processing on the first view data. Through the embodiment of the invention, the data display effect and the object experience can be improved.

The application provides a stream view classification method and device, terminal equipment and medium, the method comprises the following steps: receiving stream view data arriving in a streaming order; inputting a data view arriving at a current time into a pre-constructed evidence deep neural network model to generate a current evidence vector through a non-negative activation transformation; performing linear transformation on the current evidence vector by using a preset label transition matrix to obtain a noise-adaptive evidence vector; calculating a group of Dirichlet distribution parameters based on the noise-adaptive evidence vector, and generating a subjective logical opinion of the data view according to the Dirichlet distribution parameters; synthesizing the subjective logical opinion and a comprehensive opinion output at a previous time through a fusion operator defined based on the subjective logic to obtain a new comprehensive opinion; and determining a final classification identifier of an entity according to a belief quality vector in the new comprehensive opinion. The application can improve the accuracy of stream view classification.

Embodiments of the present application provide a training method and device of a conversion model for incomplete multi-view data, the method comprising: obtaining first description information and second description information of a sample object. First feature information and first conversion information are obtained by performing feature extraction and feature conversion processing on the first description information through a first conversion model. Second feature information and second conversion information are obtained by performing feature extraction and feature conversion processing on the second description information through a second conversion model. Model parameters of the first conversion model and the second conversion model are updated according to the first feature information, the first conversion information, the second feature information, the second conversion information, the first description information and the second description information. The technical solution of the present application can automatically generate data of a missing view according to existing view data, thereby effectively improving the accuracy of clustering processing.

The application provides a kind of multi-element stream media data acquisition method, and the method includes the following steps: step 1, obtaining the stream media source address of the stream media data to be collected; step 2, verifying the compliance of the stream media source address; step 3, collecting the stream media data by distributing the stream media source address that has passed the verification; step 4, extracting the stream media feature information from the collected stream media data; and step 5, fusing the stream media data according to the stream media feature information to obtain structured stream media data, thereby completing the multi-element stream media data acquisition.

Hybrid video decoder supporting intermediate view synthesis of an intermediate view video from a first- and a second-view video which are predictively coded into a multi-view data signal with frames of the second-view video being spatially subdivided into sub-regions and the multi-view data signal having a prediction mode is provided, having: an extractor configured to respectively extract, from the multi-view data signal, for sub-regions of the frames of the second-view video, a disparity vector and a prediction residual; a predictive reconstructor configured to reconstruct the sub-regions of the frames of the second-view video, by generating a prediction from a reconstructed version of a portion of frames of the first-view video using the disparity vectors and a prediction residual for the respective sub-regions; and an intermediate view synthesizer configured to reconstruct first portions of the intermediate view video.

The invention discloses an after-sales service SLA performance countdown monitoring system. The system comprises a multi-source performance data acquisition module, a multi-source data spectrum embedding fusion module, a performance resource scheduling calculation module, an SLA data fusion learning module, a big data performance monitoring module and a performance countdown monitoring module. The multi-source performance data acquisition module acquires multi-dimensional data such as equipment fault records and maintenance personnel scheduling information, the multi-dimensional data are fused by the multi-source data spectrum embedding fusion module and then transmitted to the performance resource scheduling calculation module to dynamically allocate resources through an algorithm, and then the SLA data fusion learning module carries out feature learning fusion on multi-view SLA data and carries out feature fusion on the multi-view SLA data. A fusion result is sent to the big data performance monitoring module for storage, retrieval and analysis, and finally the performance countdown monitoring module calculates and displays the remaining time of performance. According to the invention, the SLA performance management accuracy is improved, and reliable support is provided for after-sales service.

The application discloses a kind of gantry crane's lifting appliance pose determination method of intelligence, it includes constructing gantry crane digital model and constructing camera module, and then obtain the video sequence of gantry crane lifting appliance descent angle of view and construct gantry crane view data training set;To the angle column calibration of gantry crane view data training set, obtain calibration angle column value;View data training set is input into neural network, and angle column detection is carried out using loss function, and angle column position value is obtained;Segment angle column position value, and obtain angle column pixel space position;The depth value of lifting appliance is obtained using three-point model, and the length value of lifting appliance, width value is estimated by scale estimation, for adjusting lifting appliance pose;Through the comparison of angle column pixel space position, the depth value of lifting appliance, length value and width value of gantry crane view data training set, whether the four angle columns of lifting appliance are aligned container is judged.The present application reduces positioning error by angle column calibration and neural network training, and does not need to rely on artificial visual inspection to adjust lifting appliance.

Concepts for encoding and decoding multi-view data for immersive video are disclosed. In an encoding method, metadata is generated comprising a field indicating if a patch data unit of the multi-view data comprises in-painted data for representing missing data. The generated metadata provides a means of distinguishing patch data units comprising original texture and depth data from patch data units comprising in-painted data (e.g. in-painted texture and depth data). The provision of such information within the metadata of immersive video may address problems associated with blending and pruned view reconstruction. Also provided are an encoder and a decoder for multi-view data for immersive video, and a corresponding bitstream, comprising metadata.

The present application is directed towards systems and methods for automatically transforming reporting and view database schema during upgrading of a system from a source installation to a target installation. An analyzer executed by a processor of a client device may identify an application of a source installation configured to process a first one or more objects of the source installation. The analyzer may determine that the first one or more objects are modified during upgrading or transformation of the source installation to a target installation. The analyzer may generate a mapping between the first one or more objects of the source installation to a second one or more objects of the target installation, responsive to the determination. A transformer executed by the processor of the client device may modify a schema of the application, according to the generated mapping.

This invention belongs to the field of computer data clustering technology and discloses a multi-view clustering method, apparatus, electronic device, and storage medium. The method includes: acquiring multi-view data to be clustered, wherein the multi-view data is one of images, videos, audio, and text; determining the Laplacian matrix, depth decomposition matrix, and global consensus embedding matrix for each view based on the original data matrix of the multi-view data; performing hypergraph regularized deep non-negative matrix decomposition on each layer of the original data matrix through the depth decomposition matrix to obtain the decomposition result; performing high-level semantic alignment and consensus representation fusion on the decomposition result through the global consensus embedding matrix to obtain the final layer representation of the view; determining the clustering indicator matrix of the final layer representation according to the objective function; and processing the clustering indicator matrix using the k-means clustering algorithm to obtain the multi-view clustering result. Through the technical solution of this invention, the accuracy of multi-view clustering is achieved.

The application discloses a multi-view target tracking detection method and device, a terminal and a medium. The scheme provided by the application first inputs multi-view data obtained to an encoder module containing a specific feature reconstruction pyramid model, wherein the feature reconstruction pyramid model comprises a bottom-up network unit, a top-down network unit and a feature reconstruction unit, the feature reconstruction unit is arranged on a transverse connection channel between the bottom-up network unit and the top-down network unit, information is more efficiently fused through the feature reconstruction pyramid model, important spatial features and refined channel features are extracted, feature representation of a key region is optimized, thereby eliminating redundant information, improving the accuracy of feature aggregation, and further improving the target detection and tracking capability in a multi-view scene.

The invention discloses an urban international propagation influence multi-source data integration and structured storage method, which is realized based on a five-layer decoupling architecture originally embedded on a large language model. The method comprises the following steps: S1, collecting multi-source heterogeneous data such as social media and news, retaining original data, collecting metadata, and carrying out partitioned storage; s2, cleaning and annotating the data through a large language model, and generating a semantic-rich record containing semantic annotations and quality confidence fields; s3, constructing a topic model containing details and pre-aggregated data, and adding a data quality watermark; s4, dynamically generating a materialized view based on the query hot spot, and executing cross-source intelligent bit complementing when the data source is missing; and S5, packaging data product packages with different granularities and providing a data service interface. According to the method, efficient conversion of data from an original state to semantic enhanced assets is realized, and the method has the advantages of low cost, high precision and high adaptability.

The application discloses a kind of instruction response method and device, it is applied to target service, the target service is configured with view data source and main data source, involve database technical field.The specific embodiment of the method includes: determining the external data table required by the target service, the external data table is the data table in the database corresponding to other services;In the view data source, the mapping view corresponding to the external data table is created;Receive execution instruction for the target service, determine the target data source corresponding to the execution instruction from the view data source and the main data source;Using the target data source, respond to the execution instruction.This embodiment can simplify the operation steps of cross-library query and has higher performance.