67results about How to "Improve matching speed" patented technology

The invention discloses a construction progress detection system and method based on three-dimensional model and field data fusion, and relates to the technical field of power grid construction engineering. The system comprises a data acquisition module, a data preprocessing module, a data matching module, a data fusion module, a progress detection module and a feedback module, the data matching module matches point cloud data with a panoramic image, a clonal selection algorithm is applied to optimize matching parameters, and on-site three-dimensional basic data is constructed; the data fusion module performs deep fusion on the BIM model and on-site three-dimensional basic data, and constructs a three-dimensional fusion model for construction progress detection by using a GeoBIM technology; and the progress detection module compares the real-time acquired panoramic image of the construction site with the three-dimensional fusion model frame by frame, and automatically detects the construction progress, so that efficient acquisition, accurate processing and real-time monitoring of construction site data are realized, and the efficiency and decision ability of construction management are remarkably improved through automatic progress detection and real-time feedback.

The invention provides a data enhancement method and device, electronic equipment and a storage medium. The invention relates to the technical field of artificial intelligence, in particular to the field of data enhancement optimization, and can be applied to application scenes such as intelligent search engines, intelligent question-answering systems, enterprise knowledge bases and intelligent customer service robots. The specific implementation scheme is as follows: determining a target problem of a target domain; generating a plurality of query statements for the target question by utilizing the first language model; executing each query statement by utilizing a second language model to obtain a query record corresponding to each query statement; analyzing each query statement and the corresponding query record by utilizing a first language model to obtain candidate query statements; generating a corresponding relation based on the target question and the candidate query statement; and adding the corresponding relationship to a sample library of the knowledge question-answering system.

The invention discloses a target object pose estimation method, system and device and a medium, and relates to the technical field of pose estimation, and the method comprises the steps of offline data set establishment and online real-time multi-target pose estimation. In the off-line process, continuous RGBD streams surrounding a single object are collected, the relative poses of front and back frames are calculated frame by frame, and meanwhile, the three-dimensional surface of a target object is reconstructed to obtain a key frame off-line data set; in the online process, a visible target set in a data stream is firstly detected, VOS segmentation is performed on each target to obtain real-time effective texture and point cloud, offline key frame images of to-be-detected targets are arranged to realize single matching of all feature points and find out a closest reference frame at the same time, and RANSAC is adopted to calculate relative poses of a current frame target and the reference frame; according to the method, an expensive data labeling process is avoided, rapid integrated deployment of detection of an object without a new target is realized, the matching speed is improved, and meanwhile, online real-time multi-target pose estimation can be realized.

The invention relates to the technical field of smart home, and particularly provides a method for obtaining a clothes display image based on image recognition, an application, a control device and a medium. The method for obtaining the clothes display image based on image recognition comprises the following steps: establishing a clothes database; wherein the clothes database comprises a plurality of clothes images; acquiring a user's shot image of the to-be-displayed clothes; and determining a display image according to similarity analysis of the shot image and the clothes image. The invention further provides application of the method in clothes management. According to the invention, the quality of the display image for clothes management is improved, and the aesthetic degree is increased.

The invention discloses an attitude immune pedestrian double-magnetic speed measurement method and device, and belongs to the technical field of indoor pedestrian positioning. According to the method, a static attitude projection method is adopted, and the problems of pedestrian attitude change, magnetometer zero offset and magnetometer installation inconsistency are solved; a double-window weighted dynamic time warping algorithm is adopted, the capacity of capturing the change trend of the magnetic field is improved, the capacity of dynamically adjusting the magnetic field intensity and the contribution degree of the change trend in a cost function is improved, meanwhile, the influence of transient disappearance of the magnetic field gradient on a matching result is reduced, and the matching speed and the matching precision are improved; therefore, the pedestrian movement speed can be accurately estimated.

The embodiment of the invention discloses a geo-fence generation and matching method and device, electronic equipment and a storage medium. The method comprises the steps that intersecting hash rectangles of a target area are searched step by step according to the sequence of levels from high to low; for the searched intersecting Hash rectangles of each level, after the intersecting Hash rectangles of the current level are found, determining target intersecting Hash rectangles based on the intersecting Hash rectangles of the current level and target accuracy; and determining a fence hash code corresponding to the target area based on the target intersection hash rectangle, and generating a geo-fence of the target area based on the fence hash code, wherein the intersected Hash rectangles are geographical Hash rectangles intersected with the boundary of the target area, the area represented by the highest-level geographical Hash rectangle is the largest, and the area represented by the lowest-level geographical Hash rectangle is the smallest. According to the embodiment of the invention, the geo-fences of the target area with relatively small data volume can be quickly and accurately generated, and the matching process of the geo-fences can be quickly and efficiently carried out with relatively small calculation amount.

The invention discloses an SA-CNN-BiLSTM-based intelligent substation virtual loop automatic generation method, which comprises the following steps: in an SCD file, extracting IED equipment information of historical IED equipment and virtual terminal information contained in the historical IED equipment, and storing the IED equipment information and the virtual terminal information in a historical SCD database; forming a semantic similarity model; and based on the semantic similarity model, finding a final historical IED equipment association pair corresponding to the to-be-designed IED equipment association pair, and instantiating the to-be-designed IED equipment association pair based on the final historical IED equipment association pair. According to the method, the virtual terminator information contained in the historical SCD file is rapidly extracted in a DOM mode and stored in the database in a classified mode, and the query and matching speed is remarkably increased. The semantic similarity model can effectively extract semantic features and endow the semantic features with higher weights, the semantic recognition success rate is high, and the method has a good effect in intelligent substation virtual connection automatic design.

The invention relates to the technical field of construction progress regulation and control, and discloses a construction progress regulation and control system and method in engineering construction based on an unmanned aerial vehicle. The method comprises the following steps: firstly, acquiring an inclined image of an engineering construction site, extracting feature points by using a light beam method and an SURF algorithm, matching the feature points, and establishing an engineering construction site live-action model; secondly, clustering site clouds of the engineering construction site in combination with an engineering construction site real scene model, extracting a construction site building point cloud set, performing deviation analysis, and adjusting the engineering construction progress; a BP neural network is trained, and the engineering construction completion rate is predicted; and finally, according to the engineering construction completion rate, the engineering construction progress plan is adjusted and optimized based on a litsea rotundifolia optimization algorithm, and engineering construction progress control is realized. The purpose of regulating and controlling the construction progress is achieved by adjusting and controlling the engineering construction progress, and the method is accurate and objective.

The invention provides an automatic impedance matching method for an L-type radio frequency matcher with uniform time convergence, which combines feedforward calculation and multivariable Newton extremum search control, introduces an inverse Hessian matrix estimator, eliminates the dependence of algorithm convergence time on initial conditions and a standing-wave ratio-capacitance value function on a Hessian matrix, and improves the impedance matching accuracy of the L-type radio frequency matcher. Therefore, the convergence time is more uniform and can be freely adjusted. The convergence time can be further shortened and the initial matching condition can be optimized by adding feedforward calculation. According to the method provided by the invention, the convergence time is reduced, and the matching convergence time under different initial conditions is relatively uniform and consistent.

The invention discloses an image splicing method and device based on foreground and background segmentation. The method comprises the following steps: carrying out foreground and background segmentation on two images to be spliced, estimating a 2D rotation matrix between the two images according to angular velocity data acquired by a gyroscope, and estimating a gravity direction according to acceleration data when the two images are shot; preprocessing the images by using a rotation matrix between the two images, dividing the images into grids, and separately splicing the segmented foreground and background; according to requirements, the position of the final foreground in the background is calculated through the relative position of the foreground, fusion and splicing are carried out, and gravity correction can be selectively carried out on the final image. According to the method, the artifact problem occurring in the foreground and background image splicing is reduced, the excessive distortion of the edge is reduced, the dynamic foreground can be removed according to requirements, and the image splicing quality and accuracy are improved.

The present invention belongs to the field of project data management, and discloses a cloud-native supply chain service platform, including a demand order management module and an order matching module; the demand order management module is used to obtain the customer's demand order; the order matching module includes a database unit, a pre-matching unit, a display unit and a confirmation unit; the database unit is used to store the supplier's supply information and a set A of keywords of the supply information; the pre-matching unit is used to obtain a set B of keywords in the demand order, and calculate the matching value between the set B and the set A corresponding to each supplier, and transmit the list of suppliers with matching values ​​greater than a set threshold and the supply information to the display unit; the display unit is used to display the list of suppliers and the supply information sent by the pre-matching unit; the confirmation unit is used for the staff to select the final confirmed supplier from the list of suppliers. The present invention effectively improves the matching speed of demand orders and improves the distribution speed of the supply chain.

The invention provides a shape-based template matching method, and belongs to the technical field of machine vision, and the method comprises the steps: obtaining a plurality of template images with different scales and angles; respectively calculating the gradient, the feature vector and the feature point at each pixel point on each template image; for a test image, calculating feature vectors and feature points of the test image, performing gradient direction expansion on each feature point to obtain a gradient direction quantized value, and enabling the gradient direction quantized value to correspond to a unique binary character string; a plurality of lookup tables are created, the index number of each lookup table corresponds to each binary character string, and the index value corresponds to the cosine value of the feature point and the feature vector corresponding to the binary character string; extracting template images and feature information of the template images, performing sliding window matching on the template images on the test images in the horizontal and vertical directions, acquiring overall similarity, and judging whether the test images are successfully matched with the corresponding template images or not; according to the invention, the matching speed and accuracy can be effectively improved.

The application discloses an automatic matching embroidery thread color embroidery method for embroidery plate making, and belongs to the technical field of embroidery embroidery, and has the technical scheme as follows: S1, a numbering database is established, corresponding embroidery thread numbers are set according to the RGB values of embroidery thread colors, the numbering database is adapted to plate making software, and the numbering database is stored on a tablet computer of an embroidery machine; S2, plate making software generates embroidery plate making with embroidery thread numbers through the numbering database, and the embroidery plate making is input to the tablet computer of the embroidery machine; and S3, the embroidery plate making is read on the tablet computer of the embroidery machine, the embroidery thread numbers of the embroidery threads placed on a thread drum placing rack of the embroidery machine are identified, the embroidery threads with colors corresponding to the embroidery thread numbers in the embroidery plate making are selected, and the embroidery threads are controlled to perform embroidery. The application can improve the matching accuracy of the embroidery threads in embroidery machine embroidery processing, and ensure the matching speed of the embroidery threads.

The invention discloses a real-time monitoring method for package printing quality, and belongs to the technical field of image processing, and the method comprises the following steps: S1, collecting a package image when printing is completed, carrying out the data cleaning of the package image, and generating a package detection image; s2, inputting the package detection image into an image characterization processor to obtain an edge characterization coefficient and a local characterization coefficient, and generating a characterization group of the package detection image; and S3, completing comparison between the package detection image and the sample image of the package printing quality real-time monitoring method by using the representation group, and determining a printing quality monitoring result of the package detection image. By monitoring the image parameters in the printing process in real time, the printing quality problem can be found and solved in time, and the percent of pass and the production efficiency of printed matter are improved.

The application provides a power grid frequency modulation method and system, the method comprising: a power grid node generates frequency modulation demand information and synchronizes the frequency modulation demand information to a block chain; each EV aggregator node generates first frequency modulation resource information corresponding to the node, and if first target demand information is matched in each frequency modulation demand information according to the first frequency modulation resource information, first frequency modulation supply and demand information is generated and synchronized to the block chain; the power grid node performs device line safety checking on the first frequency modulation supply and demand information according to pre-established power grid device line information, and when the checking is passed, a first smart contract signed between the power grid node and the EV aggregator node corresponding to the first frequency modulation supply and demand information is generated, and the first smart contract is synchronized to the block chain; each EV aggregator node pushes charging and discharging task information to each electric vehicle corresponding to the node according to the first smart contract signed by the node, so that each electric vehicle accesses the power grid.

The present application provides a method for processing a sludge transfer form, which belongs to the field of data processing technology. The method includes: obtaining multiple initial images, including multiple sludge transfer form images; determining multiple target images based on an initial image, wherein the target image is a partial image in the initial image, wherein each target image includes at least one of a signature image, a date image, and a seal image; performing text recognition on the target image, and determining multiple feature data based on the recognition result, wherein the feature data includes signature data, date data, and seal data; classifying and marking multiple initial images based on the multiple feature data, and classifying the sludge transfer form images corresponding to the initial images according to the classification marks. The present application also provides a sludge transfer form processing system and an electronic device.

The invention relates to the technical field of data processing, in particular to a high-precision address data processing method and system based on named entity recognition. A high-precision address data processing method based on named entity recognition comprises the following steps: S1, preprocessing address data to obtain an address matching rule base; s2, setting a first-level address matching rule and a second-level address matching rule based on the address matching rule base; s3, acquiring address information of an alarm person, and matching the address information of the alarm person with a secondary address matching rule; and S4, obtaining a first-level address matching rule corresponding to the alarm personnel based on a matching result. By analyzing the address data of the alarm personnel, the first-level address matching rule matched with the address data of the alarm personnel is obtained, the historical alarm occurrence address of the alarm personnel or historical alarm personnel is analyzed to adjust the second-level address matching rule, and the matching speed and accuracy of the system are improved.

The application provides a multi-image array splicing method for large cement prefabricated components, and the splicing method comprises the following steps: step one: collecting original images of the cement prefabricated components, dividing the original images into regions, and adjusting the gray scale of each region to obtain preprocessed images; step two: searching for feature points between every two adjacent images in each row in the images, identifying and extracting key feature points in the images through a SIFT algorithm, and then matching the key feature points of the adjacent images through a KNN algorithm to determine the relative position relationship between the key feature points; step three: searching for feature points between every two adjacent images in each column and matching the feature points; and step four: calculating the boundary positions of each image in the splicing area, and then splicing. The application realizes high-precision splicing of the cement prefabricated components, can effectively improve the shape detection precision of subsequent cement components, and improves the product detection quality.

The invention relates to a real-time revision method and system for an interlocking relay drive and acquisition simulation rule, and the method comprises the following steps: S1, loading a BOOL operation rule definition file and a relay drive and acquisition simulation rule configuration file into an operation display subsystem, respectively determining an available relay driving code bit set and an available relay acquisition code bit set according to the BOOL operation rule definition file, and determining all initial driving code bit mapping items according to the relay driving simulation rule configuration file, the available relay driving code bit set and the available relay acquisition code bit set; s2, the operation display subsystem starts a BOOL operation simulation module and a relay simulation module, and the BOOL operation simulation module is operated based on a BOOL operation rule definition file; and the relay simulation module operates based on the drive and acquisition code bit mapping item, and provides a GUI interface for viewing and revising the current drive and acquisition code bit mapping item. According to the method, the defect of high coupling of an existing method is overcome, and the operation efficiency of the relay simulation module is improved.

The invention provides a medical safety adverse event early warning method and computer equipment, and relates to the technical field of medical information, and the method comprises the steps: obtaining early warning rules of a plurality of preset medical safety adverse events under each clinical medical business system of a target medical institution; matching a plurality of clinical medical record files of each clinical medical service system in a preset historical time period by adopting the pre-warning rule of each preset medical safety adverse event to obtain a target clinical medical record file matched with the target pre-warning rule of the target medical safety adverse event; and according to the target early warning rule and the target clinical medical record file, generating an early warning message of the target medical safety adverse event. According to the method and the device, the early warning message of the medical adverse safety event is automatically generated, and the department inpatient area with missing report is effectively supervised, so that the medical quality is improved.

The present invention discloses a cross-modal retrieval method for image-text, including obtaining an image-text pair data set and constructing a cross-modal image-text retrieval initial model; processing the image-text pair data set to obtain a feature vector; obtaining a unified dimensional feature vector of the feature vector in a common space, performing label classification and calculating the label classification loss; performing weighted sampling based on multiple negative samples on the image-text pair data set and calculating the weighted contrast loss of multiple negative samples; optimizing the cross-modal image-text retrieval initial model through an optimizer to obtain a cross-modal image-text retrieval model; and using the cross-modal image-text retrieval model to perform actual image-text cross-modal retrieval. The present invention pre-constructs a cross-modal image-text retrieval model, projects the image / text feature vector into a unified common space, introduces multiple negative sample sampling and weighted learning to perform model training, and uses the trained model to perform cross-modal retrieval; therefore, the method of the present invention has high retrieval accuracy, good reliability and fast retrieval speed.

The present invention discloses a multi-level flow table matching method and device based on Bloom filter. The method comprises the following steps: obtaining a data frame of a computer network data flow to be matched, extracting key fields from the data frame to obtain the value of the key field; inputting the values ​​of matching keywords corresponding to each level of the flow table into a preset counting Bloom filter in order of priority from high to low for detection, until the detection is passed; matching the values ​​of matching keywords corresponding to the flow table that passes the detection with a preset multi-bucket hash table based on DDR, and outputting the matching result; the device comprises a frame processing module, a serial matching module, a counting Bloom filter and a DDR memory; the present invention adopts a DDR memory to store the multi-bucket hash table, thereby increasing the flow table scale supported by the matching circuit; adopting a Bloom filter when matching flow table items, thereby reducing the number of accesses to the off-chip DDR storage and improving the matching speed of the data frame.

The invention belongs to the technical field of scene matching, and particularly relates to a rapid scene matching method for a large-range search area, which greatly improves the scene matching speed during large-range search and solves the problem of high time consumption in initial positioning of current scene matching. According to the method, a four-dimensional descriptor is firstly designed, so that the robustness of a back-end matching strategy can be greatly improved; furthermore, on the basis of the multi-dimensional reference descriptor and the multi-dimensional real-time descriptor, a convolution coarse matching and fine matching strategy is designed, firstly, the multi-dimensional reference descriptor is segmented to perform software acceleration, coarse matching is performed on the obtained nine regions by using convolution, and fine matching is performed on the obtained nine regions; cutting an image with the same size as the real-time image on the original reference image according to the matching position for accurate matching, and finally designing a matching judgment rule to judge a matching result. According to the method, a mode of combining segmentation rough matching and fine matching is adopted for a large-range search region, so that the matching speed of the large-range region is greatly improved.

The present invention proposes a non-local information matching acceleration method and device, wherein the method includes: obtaining an image to be matched, using a feature detection algorithm to obtain a feature map of the image to be matched; using a feature point detection method to extract feature point information from the feature map, extracting a sample block of the image to be matched and a feature sample block of the feature map according to the position of the feature point, wherein the sample block is an image block centered on the position of the feature point in the image to be matched, and the feature sample block is an image block centered on the position of the feature point in the feature map; using a neural network convolution layer, using the feature sample block as a convolution kernel to convolve the feature image, and calculating a global matching heat map, the global matching heat map characterizes the similarity between the sample block and each image block in the image to be matched. The present invention uses a neural network convolution layer to perform global matching of image features, accelerates the matching speed, and can perform multi-image and multi-channel parallel operations, effectively improving the speed and accuracy of non-local matching in the image processing system.

The present application discloses a biometric identification method and device, which belongs to the field of computer technology. The method includes: after acquiring a biological image under TEE, extracting biometric data in the biological image under the TEE, and then matching all or part of the biometric data with a biometric template in SE to obtain a biometric identification result. In the present application, since the security level of SE is higher than that of TEE, the biometric identification function reaches a high security level. In addition, since the calculation complexity of the template matching of biometric data is not high and the processing pressure of SE is relatively small, the template matching speed can be guaranteed to be high, thereby ensuring a high biometric identification speed. In this way, the present application enables biometric identification to be protected at a high security level while only slightly increasing the latency and without affecting the biometric identification performance, thereby improving the security of biometric identification.

The invention discloses an engineering machinery control method and control system. The method comprises the steps that an accelerator opening signal is obtained, and the target rotating speed is determined according to an engine rotating speed demand curve; the actual rotating speed of the engine is obtained in real time, the rotating speed deviation is calculated in real time, the rotating speed deviation is converted into torque, the torque is converted into oil mass, oil mass injection is conducted, the actual rotating speed is close to the target rotating speed, and the steps are repeated to form a closed loop. The method can perform locking fine control on the rotating speed of the engine, so that the rotating speed is stable and efficient, the problem of large jittering vibration of the engine is solved, oil consumption is reduced, mechanical efficiency is improved, and the service life is prolonged.

The invention relates to the technical field of artificial intelligence big data processing, in particular to a user intelligent matching method and system based on a data collision algorithm. The establishment of the user tag is the basis of intelligent matching, the basic features of the feature information are correspondingly associated with the user tag, the behavior features are specific behaviors of the user, the achievement features are results generated by the specific behaviors, and the behavior features and the achievement features are associated with the user tag through the basic features. By using a data collision algorithm, matching points can be quickly found in large-scale and multi-dimensional data. Compared with a traditional matching algorithm, the data collision algorithm can process a complex data set more efficiently, and the matching precision and efficiency are remarkably improved.

The invention belongs to the technical field of parameter optimization, and discloses a unit working condition-parameter modeling method and system. The method comprises the steps of constructing an optimal working condition table; collecting unit working condition data during operation of the unit, and marking the unit working condition data as real-time working condition data; according to the real-time working condition data, matching optimal operating parameters from the optimal working condition table; judging whether a trust instruction is generated or not according to the optimal operation parameters; if the trust instruction is generated, recommending a matched optimal operation parameter; if the trust instruction is not generated, weighting calculation is carried out on all the optimal operation parameters in the optimal working condition table, and the optimal operation parameters are obtained again and recommended; according to the method, the most similar unit working condition data can be matched from the optimal working condition table, so that the matching speed and the matching precision are improved; and intelligent recommendation of the optimal operation parameters is realized, so that the overall operation efficiency and the quality index of the unit are improved, and the adaptability, the robustness and the safety of the system are enhanced.

The invention provides a configuration method of a Kong gateway. The method comprises the following steps: packaging a cardinality tree routing collection function, a cardinality tree construction function and a cardinality tree query function; embedding the cardinal number tree routing collection function and the cardinal number tree construction function into an initialization function of the Kong gateway, so that the cardinal number tree routing collection function is utilized to obtain cardinal number tree routing information corresponding to each piece of native routing information when the native routing information in the database is traversed in the initialization process of the Kong gateway, and the cardinal number tree routing information is obtained by the cardinal number tree routing collection function. Obtaining a target cardinal number tree according to the routing information of each cardinal number tree by utilizing a cardinal number tree construction function; and replacing the routing matching code in the routing query function of the Kong gateway with the cardinality tree query function, so that when the Kong gateway receives the query request, if the matching is not successful in the cache, the cardinality tree query function is utilized to process the query request. According to the scheme, the Kong gateway can adopt the cardinal number tree as a core data structure for route matching, memory use is optimized, and the overall performance is remarkably improved.

The invention discloses a natural gas supply and demand matching method based on a smart contract, and particularly relates to the technical field of block chains, and the method specifically comprises the steps: building a prediction model through a machine learning algorithm, carrying out the optimization of the smart contract according to the prediction model, transmitting external data to the smart contract through an integrated oracle machine, and carrying out the optimization of the smart contract. Performing primary evaluation according to the external data to verify an applicability condition matched with the transaction, and performing secondary evaluation on the smart contract to verify the real-time performance of the smart contract when the applicability condition does not meet a preset applicability limit; when the real-time performance of the intelligent contract is insufficient, a state channel is introduced to carry out under-chain transaction, a transaction result is transferred to the chain to carry out verification settlement through the intelligent contract, natural gas supply and demand matching is carried out according to the introduced state channel, and payment settlement is carried out on the transaction through the chain after matching is completed, so that the flexibility of the intelligent contract is improved; and the transaction security is improved while the transaction cost is reduced.