127 results about "Data registration" patented technology

The invention discloses a smart city planning three-dimensional scene reconstruction optimization system combined with semantic segmentation, and belongs to the technical field of three-dimensional scene reconstruction optimization. The system comprises a data sensing module which collects aerial images and laser point clouds, and complements a sheltered area to obtain city modeling data; the preprocessing module performs denoising, data registration and data fusion on the city modeling data to generate texture point cloud data; the semantic understanding module realizes multi-modal semantic segmentation of the texture point cloud data through a fine-tuned SAM network and an improved RandLA-Net, and semantic tag data is obtained through restoration and optimization; the reconstruction optimization module constructs an initial three-dimensional grid model based on the texture point cloud data, and optimizes a ground feature boundary and a missing region of the model in combination with a semantic tag; and the output application module converts the optimized model into a standard format and outputs the model. Through deep coupling of semantic segmentation and reconstruction optimization, the precision of the three-dimensional scene model is improved, and reliable support is provided for smart city planning.

Systems, methods, and computer readable media for routing inputs on a extended reality (XR) wearable device where the methods performed on an apparatus of a system include receiving, at an input framework service, an input data registration request from a client component, the input data registration request comprising an indication of a callback component and an indication of input data having a type, and verifying, at the input framework service, the client component is authorized to access the input data having the type. The method may further include registering, at the input framework service, the callback component with an input service associated with the input data having the type, receiving, at the input service, input data having the type, and invoking, at the input service, the callback component.

The invention discloses a focus intelligent detection and diagnosis system based on multi-modal medical image fusion, and relates to the technical field of medical image processing. A molybdenum target image, an ultrasonic image and a magnetic resonance image of the mammary gland of the patient are acquired through the data acquisition module; a data registration module is used for carrying out partition affine and local refinement registration on the multi-modal image by taking the molybdenum target image as a geometric anchor point and combining parameters such as compression force; extracting registered fusion feature data through a data fusion module; generating a candidate focus set by a focus detection module; finally, the risk assessment module calculates a comprehensive risk score through weighting, correction and consistency verification processes based on a plurality of interpretable feature indexes. And the output module generates a visual diagnosis result. According to the invention, intelligent detection and risk assessment of rechecking of breast lesions are realized, and the diagnosis accuracy and clinical reliability are effectively improved.

The invention discloses a power distribution network inspection robot system and method, and relates to the technical field of intelligent inspection, and the system comprises a data collection module, a data registration module, an anomaly detection module, a space verification module, a time sequence analysis module and a comprehensive judgment module. The data acquisition module controls the robot to acquire multi-modal data and record space-time positioning information; the data registration module registers the multi-modal data to an equipment coordinate system; the anomaly detection module extracts anomaly features and calculates confidence; the space verification module carries out space consistency verification and physical logic consistency verification according to the physical rule base and evaluates the abnormal level; the time sequence analysis module evaluates a defect evolution state; and the comprehensive judgment module performs defect judgment and generates a processing strategy. According to the method, single-mode false detection and environmental interference are effectively eliminated through a dual verification mechanism, comprehensive evaluation of the current state and the development trend of the defect is realized in combination with time sequence evolution analysis, and the accuracy and the reliability of defect detection are remarkably improved.

The invention relates to the technical field of agricultural intelligent equipment, in particular to intelligent monitoring and weeding equipment for gramineous weeds in a winter wheat field, and aims to solve the technical problem of high missing detection rate and false detection rate of a traditional visual identification method caused by similar forms of winter wheat and gramineous weeds in a seedling stage. The equipment comprises an autonomous mobile platform, a multi-mode sensing assembly, a data processing and decision-making unit and a targeted clearing execution mechanism. The multi-mode sensing assembly integrates a hyperspectral imaging module, a three-dimensional shape measurement module and a polarization characteristic analysis module, and pixel-level data registration is achieved in combination with the cooperative illumination system. The data processing unit performs high-confidence classification decision on the multi-source features through a hierarchical Bayesian fusion model; and the targeted clearing mechanism adopts a laser galvanometer system to carry out non-contact precise clearing on the identified weed growing points. Intelligent identification and efficient physical weeding of weeds in the winter wheat field are achieved, and the method has the advantages of being free of chemical residues and high in operation continuity.

The invention provides tunnel lining disease AI detection and positioning equipment, which relates to the technical field of tunnel engineering detection and comprises a data acquisition module, an edge calculation module and a cloud analysis module. According to the invention, the appearance image data, the three-dimensional point cloud data and the thermal imaging data of the tunnel lining are synchronously acquired through the multi-sensor array carried on the mobile carrier, unmanned continuous automatic detection can be realized, manual processing of subsequent mass data is avoided, then an end-side-cloud collaborative architecture is introduced, and the real-time performance of the tunnel lining is improved. The edge calculation module is responsible for real-time identification and preliminary positioning to ensure the detection efficiency, and the cloud analysis module maps two-dimensional disease information to a three-dimensional space through a multi-source data registration and fusion algorithm to accurately calculate the geometric dimension and absolute coordinates of the disease information. Meanwhile, in combination with thermal imaging data analysis, recessive diseases which cannot be found by a traditional method are effectively identified. According to the method, human eye interpretation is replaced by the artificial intelligence model, so that the objectivity and consistency of results are ensured.

Systems, methods, and computer readable media for routing inputs on a extended reality (XR) wearable device where the methods performed on an apparatus of a system include receiving, at an input framework service, an input data registration request from a client component, the input data registration request comprising an indication of a callback component and an indication of input data having a type, and verifying, at the input framework service, the client component is authorized to access the input data having the type. The method may further include registering, at the input framework service, the callback component with an input service associated with the input data having the type, receiving, at the input service, input data having the type, and invoking, at the input service, the callback component.

A data registration apparatus (200) processes original data saved in a data source and registers the processed data. A data verification apparatus (300) computes a digest value of reference combined data which is generated based on a digest value of the original data and a digest value of the processed data as a reference digest value. The data verification apparatus computes a digest value of the registered processed data as a provisional digest value, retrieves digest value saved in the data source as a provisional digest value, computes a digest value of verification combined data which is generated based on the provisional digest value of the original data and the provisional digest value of the processed data as a verification digest value, and compares the verification digest value with the reference digest value.

This application provides a method, apparatus, device, and medium for determining joint calibration parameters. In this method, a calibration board is placed in different poses. For each pose, based on the edge line of the calibration board in the image acquired by the camera at that pose, the first coordinates of a preset position on the calibration board in the image are determined. Then, the point cloud data at that pose is processed using a plane fitting algorithm to obtain a first plane corresponding to the calibration board in the point cloud data acquired by the LiDAR. Based on the laser point located on the edge line of the calibration board and the determined first plane, the second coordinates of the target laser point at the preset position on the calibration board are determined. Based on the determined first and second coordinates of each pose and a preset data registration algorithm, the parameters for joint calibration of the camera and LiDAR are comprehensively determined, mitigating the problem of low accuracy in determining calibration parameters caused by error accumulation.

The invention discloses a human body scanning data registration method and device, equipment and a medium, and relates to the technical field of computer vision. The method comprises the following steps: acquiring a full-head 3D scanning point cloud, a side face 3D scanning point cloud and an in-ear 3D scanning point cloud; human ear 3D scanning point clouds are extracted from the full-head 3D scanning point clouds and the side face 3D scanning point clouds, and first human ear 3D scanning point clouds in the full-head 3D scanning point clouds and second human ear 3D scanning point clouds in the side face 3D scanning point clouds are obtained; determining a first spatial conversion relation and a second spatial conversion relation according to the in-ear 3D scanning point cloud, the first human ear 3D scanning point cloud and the second human ear 3D scanning point cloud; wherein the first space conversion relation is a coordinate conversion relation between the full-head 3D scanning point cloud and the side face 3D scanning point cloud, and the second space conversion relation is a coordinate conversion relation between the in-ear 3D scanning point cloud and the side face 3D scanning point cloud. The method provides a new human body scanning data registration method.

The application belongs to the technical field of intelligent detection of building engineering, and particularly relates to an automatic defect identification system for fabricated buildings based on an unmanned aerial vehicle, which comprises a data acquisition module, a data registration module, a sleeve positioning module, a feature extraction module, a defect identification module and a report output module. The system collects multi-source heterogeneous data through the unmanned aerial vehicle, constructs a time-sequenced three-dimensional data field, eliminates the influence of environmental interference through pretreatment, extracts visible light image features, infrared thermal imaging features and three-dimensional point cloud geometric features in parallel, realizes comprehensive diagnosis of the internal and external filling state of grouting, accurately identifies insufficient hollows of grouting, late shrinkage hollows and defects of insufficient vertical depth of grouting, simultaneously carries out dynamic tracking, accurate quantification and tracing, effectively solves the problems that the existing detection of the filling state of sleeve grouting of fabricated buildings is single in dimension, poor in space-time continuity, weak in environmental adaptability and difficult to accurately quantify and trace defects, and improves the intelligent reliability of quality control.

The invention discloses a tunnel face integrity evaluation method based on deep learning, and the method comprises the steps: firstly scanning a tunnel face through a laser radar carried on an unmanned plane, obtaining a point cloud file of the tunnel face, and carrying out the data registration, data noise reduction, data simplification and three-dimensional modeling of the point cloud file through a data processing technology; the method comprises the following steps: performing tunnel face image extraction and image preprocessing on a three-dimensional model obtained after data processing, performing crack identification through a YOLOv5 convolutional neural network, and performing enhancement and structure optimization on crack image features through operations such as image segmentation, image noise reduction, crack skeleton extraction, edge detection, crack skeleton line splicing and the like. And information such as crack width and crack length is obtained through the processed image. The face fracture density and the ratio of open, micro-open and closed fractures are calculated through the information, the face fracture density is used for distinguishing the completeness and local stability of the tunnel face rock mass, and the completeness and local stability of the tunnel face are evaluated more comprehensively through the ratio of the three fractures.

The application relates to the computer technical field and discloses a tooth three-dimensional precision correction method and system for multi-source oral data fusion, aiming to solve the problems of low multi-modal oral data registration precision, serious geometric distortion and lack of function-oriented optimization in the prior art. The method comprises the following steps: synchronously acquiring intraoral scanning, CBCT and facial three-dimensional point cloud data; performing format conversion, denoising and grid simplification preprocessing; extracting tooth surface morphology, root canal anatomy and soft tissue contour features and encoding them into a unified feature tensor; and realizing multi-modal data space alignment through phased rigid and non-rigid registration. Through the above scheme, the multi-source data fusion precision and tooth morphology restoration accuracy are significantly improved, full-process automatic and efficient processing is realized, and the clinical real-time and high-precision diagnosis and treatment requirements are met.

The invention provides a magnetocardiogram data current source feature extraction method, system and device and a medium. The method comprises the steps of obtaining target data; the target data comprises magnetocardiogram data and heart model data; performing data registration according to the magnetocardiogram data and the heart model data to obtain fusion data; performing inverse problem solving on the fusion data according to a point source reduction algorithm to obtain a comprehensive current source of the heart model; and extracting characteristic parameters according to the comprehensive current source to obtain target characteristic parameters. According to the method, data registration is carried out on the magnetocardiogram data and the three-dimensional heart model data to obtain the fusion data, inverse problem solving is carried out on the fusion data through a point source reduction algorithm, the current source on the heart model corresponding to the magnetogram at the moment is solved, distinguishable index parameters are further mined according to the current source, and therefore the accuracy of the heart model is improved. The indexes start from the angle of a current source instead of a magnetic graph or a waveform, so that the mining angle is more comprehensive, and the analysis result is more accurate.

The invention provides a method for quickly checking an oblique photography model, and relates to the technical field of image processing. Comprising the following steps: S1, acquiring an oblique photography model, a digital orthoimage, a digital surface model and high-precision control point data, judging a topographic type of a measured area based on DSM elevation mutation parameters, and correspondingly executing format conversion, noise removal and hierarchical data registration to form a standardized auditing data set adapted to topographic features; s2, based on the preprocessed data set, synchronously executing time-space cooperation precision detection and feature fusion integrity and compliance detection, and introducing a three-dimensional evaluation model to complete dynamic risk level evaluation; s3, generating a visual auditing report containing a dynamic label; the problems of complex terrain adaptation, risk assessment and closed-loop efficiency in the prior art are solved, the multi-dimensional detection coverage rate is increased, the risk identification accuracy is improved, the auditing and rectification closed-loop efficiency is improved, the labor cost is reduced, and the scene adaptability is improved.

Embodiments of the present disclosure disclose a point cloud data registration method and device, electronic equipment and computer program product, the method comprising: obtaining at least two pieces of point cloud data to be registered; the at least two pieces of point cloud data are collected for the same collection area, and at least three calibration balls are fixedly placed in the collection area during the collection process; converting the point cloud data into image data; identifying the image area corresponding to the calibration ball from the image data; matching the calibration ball identified in the image data corresponding to the at least two pieces of point cloud data based on the relative position relationship of the at least three calibration balls in the image data; and registering the at least two pieces of point cloud data based on the matching result. This technical solution directly identifies the image, and then registers the point cloud data based on the information identified from the image, which can reduce the labor cost, improve the processing efficiency of the point cloud data, and also improve the accuracy and efficiency of the point cloud data registration.

The application relates to the technical field of data processing, and discloses a multi-source pipeline data registration and fusion labeling method for heterogeneous coordinate systems, which comprises the following steps: obtaining multi-source pipeline data and source coordinate system description information to establish a coordinate transformation model. Pipeline nodes, pipeline sections, connectivity relationships and semantic attributes are extracted, source and target pipeline network topology semantic constraint graphs are constructed, a registration error model is established, parameters are jointly solved through iterative optimization, and a globally consistent registration result is obtained. Pipeline nodes and pipeline sections from different pipeline data sources and corresponding in spatial position, topology structure and semantic attributes are clustered into unified pipeline objects and assigned with unified identification. A quality-driven attribute fusion model is constructed, geometric attributes are corrected within engineering constraints, classified attributes are weighted, and finally, a fusion labeling result is obtained. The application obtains unified pipeline objects which are globally consistent, topologically correct, semantically unified and provided with quality labeling.

This invention provides a multimodal fusion-based method for correlation analysis of deep-sea environmental data outside the Yangtze River Estuary, belonging to the field of deep-sea environmental analysis technology. This invention achieves accurate data registration by establishing a spatiotemporal standardization model for multi-source data and employing an adaptive spatiotemporal kriging interpolation algorithm. It utilizes a sparse coding marine signal separation algorithm to construct an overcomplete dictionary to separate mixed signals and extract pure features. Based on an attention mechanism, a feature extraction network is constructed to automatically learn deep feature representations of physical, chemical, and biological parameters. A matrix rank deficiency detection algorithm is used to automatically supplement feature compensation vectors to ensure feature integrity. A cross-scale attention mechanism based on wavelet transform is constructed to fuse multi-scale features. A Shapley value interpretability evaluation system is established to quantify the importance of correlated features. This invention solves the technical problem of inaccurate correlated feature extraction during the fusion of multi-source heterogeneous marine environmental data.

The invention discloses an FPSO (Floating Production Storage and Offloading) intelligent directional spraying method based on multi-sensor fusion, which is suitable for fire prevention and control of an FPSO upper module. The method comprises the following steps: firstly, dividing protection sub-areas, arranging infrared, ultraviolet, visible light and attitude sensors, matching with mixed nozzles and networking; establishing a module coordinate system, and completing sensor calibration and multi-modal data registration; and a multi-task CNN fire identification model is constructed, and fire source positioning, type discrimination and spreading prediction are realized. When the system operates, image stabilization is performed through hull attitude compensation, fusion feature input models are extracted, and personalized fire extinguishing strategies are generated; and generating a spraying instruction through space calculation and the like, driving the nozzle to spray in a directional and constant-flow manner, and dynamically optimizing the strategy based on real-time feedback until the fire is extinguished. Point-to-point fire extinguishing is achieved, water stain loss and fire fighting water waste are reduced, and the accuracy and efficiency of fire fighting in the marine environment are improved.

The application provides a railway full-line track state determination method and device, relates to the field of track vehicle safe operation state evaluation, and comprises the following steps: performing space-time data registration on operation state time series data of a track vehicle and corresponding line space position data to obtain a space-time data set; performing space-time feature extraction on the space-time data set to generate corresponding space-time feature values; inputting the space-time feature values into a pre-constructed railway full-line track state prediction model to obtain a railway full-line track state; and wherein the railway full-line track state prediction model is pre-constructed according to historical operation state time series data and corresponding historical line space position data. The application can predict the railway full-line track state.

A high-precision three-dimensional automatic modeling method for a substation, comprising: collecting laser point cloud data of a substation and multi-view images of the substation; performing dense point cloud data registration, camera parameter reconstruction for the multi-view images, projection of the multi-view images, and adaptive point cloud density control; using three-dimensional Gaussian distribution functions to approximate the point cloud data, summing all the three-dimensional Gaussian distribution functions to obtain a Gaussian distribution geometric field of a three-dimensional Gaussian distribution point cloud representation, and obtaining a three-dimensional mesh model by means of three-dimensional mesh reconstruction and rendering; setting constraint conditions of devices on the basis of the three-dimensional mesh model, and using a volume segmentation algorithm and a three-dimensional labeling algorithm to generate a three-dimensional device model, device coordinates, and device category names; and converting the device model into a GIM file, generating a PMS file from the device coordinates and the device category names, and synchronizing the files to a GIM and PMS3.0. The present invention can effectively solve the problems of low efficiency and inconsistent quality in conventional manual modeling processes.

This invention relates to a markerless real-time registration and tracking method and system for mandibular surgery. The method includes the following steps: the patient performs multiple opening and closing movements of the upper and lower jaws while the robotic arm is fixed, and the system synchronously records the changes in the angles of each joint of the robotic arm; based on the forward kinematics of the robotic arm, the continuous motion trajectory of the distal end of the jaw in space is calculated to form an actual jawbone trajectory point cloud; a preoperative image model is formed using the actual jawbone trajectory point cloud, a simulated jawbone trajectory is constructed in the preoperative image model, and the actual trajectory is aligned using the ICP registration algorithm to achieve automatic registration; the system establishes a mapping between angle changes and the spatial posture of the jawbone to achieve dynamic tracking and visual navigation during surgery. This invention solves the problems of large errors, high complexity, many limitations, and low efficiency in preoperative image data registration technology during maxillofacial surgery, avoids the need for preoperative implantation of markers, and achieves high-precision registration, high automation, and strong real-time performance under natural conditions.

This invention discloses a method and system for predicting deformation during the fabrication of turbine blade module shells based on a two-level nested graph neural network, belonging to the field of digital control technology for aero-engine turbine blade manufacturing. The method includes acquiring a large module CAD model, finite element simulation results, and CT scan data; performing multi-source data registration and fusion to obtain unified multi-source data features; constructing a two-level nested graph structure based on the multi-source data features; and inputting the two-level nested graph structure into a nested graph neural network model for sintering deformation prediction. This invention integrates the CAD geometric model and finite element simulation results, mapping high-density simulation data to sub-graph nodes using spatial interpolation technology; employing a nested graph neural network for hierarchical feature extraction, enabling each blade to learn its own local deformation pattern and perceive its positional context within the module; finally, outputting the three-dimensional deformation prediction values ​​for each sampling point, and visually marking high-risk areas to assist in process optimization decisions.

The application discloses a SA network access method, system and device based on a 5G Internet of Things card and a medium, and comprises the following steps: an IMS registration request is initiated to a visited 5G core network through a user terminal, and IMS registration is completed through a visited IMS core network element ICSCF and a home IMS core network element ICSCF; an SA data registration request is initiated to the visited 5G core network through the user terminal, and SA data registration is completed through a visited AMF and a home UDM according to Internet of Things card information of the user terminal; a 5G session request is initiated to the visited AMF through the user terminal, and authorization authentication is performed on the 5G session request through an SMF; session policy information is determined through the SMF, and the session policy information is issued to a UPF, so that the user terminal accesses a required external network through the UPF. The application can solve the problem that some terminals cannot access an SA network compatible with a 5G Internet of Things card, and can be widely applied to the technical field of Internet of Things.

The embodiment of the application provides a pig carcass intelligent grading method and device based on multi-modal feature fusion, through multi-sensor synchronous acquisition and multi-modal registration preprocessing, cross-modal attention fusion and backfat value enhancement comprehensive feature construction, and grading result evidence and production line diversion linkage, effectively solves the deficiencies of traditional technology in multi-modal data registration, feature fusion and closed loop linkage, and provides technical support for intelligent and accurate grading of pig carcass.

The challenge is to provide a workflow management system that is suitable for use in actual business operations. [Solution] A workflow management system, A display unit that shows the workflow generation screen, A generation unit generates a workflow related to the workflow based on the generation instructions entered via the workflow generation screen, A data registration unit, upon receiving an instruction to execute a workflow, generates execution information including the execution status of one or more steps included in the workflow and registers it in association with the workflow. The display unit displays a screen showing the flowchart of the workflow and the execution status. Two or more of the aforementioned execution information are associated with the workflow. Workflow management system.

The present application relates to oral cavity 3D data scanning technology, and discloses a 3D data registration method for oral cavity scanning, comprising: constructing a voxel model based on real-time oral cavity scanning point cloud data, frame-by-frame registering real-time oral cavity to-be-registered point cloud data and the voxel model, if the real-time oral cavity to-be-registered point cloud data and the voxel model fail to be registered for a continuous preset number of frames, selecting a to-be-registered voxel set from the voxel model through a pre-constructed repositioning method, if the real-time oral cavity to-be-registered point cloud data and the voxel model fail to be registered for a continuous preset number of frames, selecting a to-be-registered voxel set from the voxel model through a pre-constructed positioning method, performing point cloud coarse registration processing and point cloud fine registration processing on the real-time oral cavity to-be-registered point cloud data and the to-be-registered voxel set, and obtaining a registration result. The present application also proposes a 3D data registration device and equipment for oral cavity scanning and a storage medium. The present application can improve the speed and accuracy of oral cavity scanning data registration.

The application discloses a lake and reservoir algae bloom prediction and monitoring time window scheduling method, equipment and storage medium, comprising: based on observation data, using a data assimilation algorithm to perform online assimilation update on the state and parameters of the lake and reservoir digital twin; using the assimilated digital twin to predict the algae bloom in the future period, and performing physical constraint correction and uncertainty quantification processing on the prediction result to output prediction information; generating a detection time window candidate set according to the prediction information; based on the detection time window candidate set and a preset operation constraint, optimization solving is performed to obtain a detection time window scheduling strategy, which is issued to an unmanned detection platform, and the measured data collected after the execution of the base detection task is fed back to the observation data to perform data registration and model assimilation on the digital twin. Through the construction of a closed-loop system of perception-assimilation-prediction-scheduling-feedback, the application realizes dynamic optimization configuration of monitoring resources according to the algae bloom risk, and improves the early warning timeliness and resource utilization efficiency.

The invention discloses an automobile interior and exterior decoration detection method and system based on visual fusion, and relates to the field of automobile door installation and detection. The method comprises the steps of obtaining and preprocessing two-dimensional image data and three-dimensional point cloud data, obtaining a spatial transformation matrix through data registration and generating a three-dimensional edge guide line, clustering and segmenting a vehicle door point cloud set and a vehicle body point cloud set based on the three-dimensional edge guide line, calculating surface difference data and gap data, and obtaining a vehicle door point cloud set and a vehicle body point cloud set; and comparing the surface difference data with the gap data and the tolerance, and generating a detection report. According to the method, the advantages of multi-modal data are fused, the problems of inaccurate edge identification, low measurement precision and the like caused by surface reflection and low texture interference of a traditional single detection method are effectively solved, and high-precision and automatic detection of the automobile door gap surface difference is realized.

The utility model discloses a portable data statistics auxiliary device for performance evaluation of detection equipment, which relates to the technical field of data statistics, and comprises a form paper supporting mechanism, a page turning paper pressing mechanism, a sheet paper fixing mechanism, a sheet paper pressing mechanism, a sheet paper pressing mechanism, a sheet paper pressing mechanism, a sheet paper pressing mechanism, a sheet paper pressing mechanism and a sheet paper pressing mechanism, wherein the sheet paper supporting mechanism is used for mounting the sheet paper fixing mechanism and the page turning paper pressing mechanism; the form paper fixing mechanism is used for pressing and fixing the bound form paper; the page turning paper pressing mechanism comprises a rotating shaft, a sleeve, a torsional spring, a shifting plate and an L-shaped pressing plate; and the rotating shaft is rotationally embedded in the inner side of the mounting groove through a bearing, and the sleeve is fixedly arranged in the middle of the outer side of the rotating shaft in a sleeving mode. According to the utility model, the sheet paper can be blocked and limited after page turning, so that the condition that the sheet paper is blocked due to resetting in the subsequent data registration process is avoided, and the sheet paper is more convenient in actual use.