213 results about "Projection model" patented technology

The invention discloses an on-orbit spacecraft attitude estimation method and system based on ISAR image feature selection, and belongs to the field of aerospace control systems. The method comprises the following steps: acquiring an ISAR image of a spacecraft, and acquiring a complex linear structure set and three-dimensional feature points of an on-orbit spacecraft; then, according to the obtained three-dimensional-two-dimensional projection model, the CRLB of each reference structure in the complex linear structure set is deduced to carry out attitude estimation error analysis; calculating the trace of the CRLB covariance matrix of each reference structure to select an optimal feature structure, correcting the scattering point trace of the optimal feature structure by using polynomial fitting, and switching the reference structures as a new optimal feature structure according to the scattering point loss rate and a preset sequence; and optimizing the spacecraft attitude angle solving function by using a particle swarm and LM hybrid algorithm to obtain attitude angle parameters. The target with high-precision target attitude real-time estimation can be completed aiming at the problems that high-order frequency change in a dynamic environment is difficult to capture and resolution and noise suppression are contradictory due to a fixed window time-frequency analysis method.

The invention relates to a large language model dynamic routing method and device based on context learning model characterization and a readable storage medium. Query is embedded and mapped to a language model input space by using a projection model, semantic alignment is realized, a representative evaluation set covering multi-dimensional capability is automatically screened from a benchmark question bank, and the representative evaluation set is used for evaluating the multi-dimensional capability. Performance characteristics of the model on an evaluation set are efficiently obtained at a time, and high-quality context model capability representation is formed; then real-time query embedding and context model capability representation are combined, a lightweight routing language model is used for supervised learning, so that the fine-grained model distinguishing capability is achieved, an increment embedding updating mechanism is designed, and when a new model is accessed or an old model is upgraded, cold start can be rapidly completed only through a very small number of fixed questions, so that the efficiency is improved. The calculation and maintenance cost is greatly reduced, and the accuracy, real-time performance and flexible expansibility of model routing are effectively improved.

The invention provides a low-earth-orbit satellite global beam position distribution and scheduling system based on deep reinforcement learning, and the system comprises a low-earth-orbit satellite scene modeling beam position distribution module which is used for constructing a low-earth-orbit satellite communication scene and completing the global beam position division. A satellite constellation configuration and orbit parameters are set, global beam positions are divided based on a spherical network, a beam ground projection model and a user system model are established, and a scene basis and a beam position division basis are provided for beam resource scheduling; the deep reinforcement learning beam resource scheduling module is used for realizing intelligent allocation scheduling of beam resources, establishing a decision system based on a Markov decision process by constructing a beam resource allocation model, extracting features through a state space model, performing time sequence modeling, and optimizing a scheduling strategy based on deep reinforcement learning. And dynamically matching the user demand and the beam resource. Therefore, dynamic optimization of low-orbit satellite beam resources is realized, the resource utilization rate is improved, and the communication requirements of users are efficiently met.

The invention discloses a construction method based on a Chinese poem-semantic knowledge graph, and particularly relates to the technical field of graph reasoning. The method comprises the following steps: dividing a poem text into a plurality of feature sub-channels according to style dimensions such as rhythm, rhyme, image, allusion and the like, extracting a heterogeneous style feature vector group, and generating an affiliation probability matrix by using a style fingerprint projection model; generating a style mixing label under an affiliation fuzzy condition, and realizing style affiliation reasoning based on atlas embedding and semantic path traversal; if the style boundary sample exists, triggering an atlas structure self-updating mechanism to realize extension and boundary learning of style nodes; the method effectively improves the accuracy and interpretability of Chinese classical poem style affiliation and the adaptive ability of the map structure, and is suitable for scenes such as poem style analysis, author affiliation judgment and style evolution modeling.

The invention discloses an unmanned aerial vehicle dynamic projection map construction method and system based on spatio-temporal data fusion, and belongs to the technical field of unmanned aerial vehicle video monitoring and geographic scene fusion, and the method comprises the steps: obtaining multi-modal flight data in real time based on an unmanned aerial vehicle, and the multi-modal flight data comprise video image data and spatio-temporal reference data; and performing data preprocessing on the multi-modal flight data to obtain route data. And constructing an unmanned aerial vehicle dynamic projection model, and performing space-time synchronous projection rendering on the route data to obtain an unmanned aerial vehicle dynamic projection map. And constructing a dynamic calibration model, and correcting the dynamic projection map of the unmanned aerial vehicle. According to the method, an integrated dynamic geographic information sensing system is constructed through deep cooperation of a spatio-temporal data fusion framework and an intelligent calculation engine, accurate mapping of the geographic space driven by spatio-temporal reference fusion is realized, millimeter-level space registration capability is constructed through multi-modal data intelligent solution and terrain adaptive rendering, and the real-time dynamic geographic information sensing system is constructed. And a technical breakthrough is formed in the dimensions of accurate positioning, data fusion, real-time response and the like.

A space-time learning and lightweight direct-current optimal power flow projection scheduling method driven by a reactance perception graph kernel comprises the steps that the reactance perception graph kernel based on a susceptance matrix is constructed, a power grid node reactance perception spatial dependency relationship is extracted, and multi-period node feature tensors are organized; a space-time learning device comprising a graph convolution encoder and a time sequence encoder is adopted to carry out space-time joint modeling on the node features, and the cross-time evolution law of the node marginal electricity price and the voltage phase angle is learned; mechanism consistent physical regular terms of load flow safety and climbing consistency are introduced in training, and physical constraint influences are gradually enhanced by means of weight scheduling; and converting the phase angle trajectory into an equivalent unit output initial value through physical mapping, constructing a lightweight quadratic programming projection model with the minimum deviation initial value, and generating a feasible day-ahead scheduling plan under the constraint of meeting power balance and the like. According to the method, the whole link from prediction to scheduling is opened, the speed and the reliability are both considered, and an engineering available path is provided for day-ahead multi-period clearing and large-scale scene analysis.

The invention discloses a visual camera calibration method and system applied to large-view-field optical measurement, and belongs to the technical field of visual measurement, and the method comprises the steps: firstly obtaining a multi-view-angle image sequence and a camera three-dimensional position corresponding to each frame of image; obtaining an initial camera external parameter with a real scale and a three-dimensional scene structure through a motion recovery structure and in combination with a camera position; selecting and initializing a large-view-field camera projection model containing an internal reference matrix and a lens distortion parameter; iteratively optimizing lens distortion parameters, camera external parameters and three-dimensional point coordinates; and constructing and minimizing a global cost function containing a re-projection error and camera position constraint, and jointly optimizing all parameters to obtain a final calibration result. According to the method, through comprehensive model optimization, by applying surveying and mapping services except satellite application services, the calibration precision and model completeness of large-view-field complex distortion are remarkably improved, and the problem that distortion correction is insufficient due to dependence on a few points is solved; and the robustness and the intelligent level of calibration and the reliability and the traceability of a result are improved.

A method for previewing the terrain in front of an emergency rescue vehicle in a geometric feature degradation scene relates to the technical field of road surface recognition, realizes accurate alignment of LiDAR point cloud and IMU data through timestamp synchronization and linear interpolation, and combines a spherical projection model and a degradation perception complementary feature selection algorithm to realize the previewing of the terrain in front of the emergency rescue vehicle. Converting the three-dimensional point cloud into a robust intensity image and extracting gradient significant features; based on a double-observation secondary filter frame, a motion state is predicted by utilizing IMU forward propagation, a point cloud geometric residual error and an intensity image luminosity residual error are synchronously fused, timestamp deviation is compensated through back propagation, and a multi-source observation model under a global coordinate system is constructed. Finally, the error state is iteratively optimized to realize collaborative output of the high-precision odometer and the three-dimensional terrain map, and the problems of data asynchronism, feature degradation and dynamic interference in a complex scene are effectively solved.

The embodiment of the invention provides a multi-view-angle-based stage fusion panoramic look-around image generation method and device, equipment and a computer readable storage medium. The method comprises the following steps: acquiring a target image through a target fisheye camera; constructing a multi-view spherical projection model according to the target image; and according to the spherical projection model, generating a target visual angle panoramic spliced image. In this way, the problems of geometric distortion, obvious edge seams, inconsistent brightness, texture information loss and the like existing in a traditional double-fisheye image splicing method are solved.

Systems and methods for intuitive search and recommendation including a content comprehension engine executing on a computer processor and configured to: receive a recommendation request identifying a source content item; generate a first embedding for the source content item in a first embedding space from content metadata and contextual data; apply a trained neural projection model to map the first embedding to a second embedding space, thereby producing a projected embedding; compute, for content item models stored in a repository, a similarity score between the projected embedding and the content item model, each content item model including word-vector collaborative-filtering representations of an available content item; select, based on the similarity scores, a subset of the content item models; and output a result set including the available content items corresponding to the subset and ordered by the similarity scores.

The first aspect of this application proposes a method for fusing laser point cloud and visible light image, including: S1, performing spatial dimensionality reduction on the point cloud data to obtain two-dimensional point cloud data; S2, extracting feature points of the two-dimensional point cloud data and feature points of the visible light image data through the Scale-Invariant Feature Transform (SIFT) algorithm; S3, determining the projection plane, projecting the point cloud data through the projection model to generate a depth-echo intensity image, and constructing a 3D-2D coordinate mapping relationship between the point cloud data and the depth-echo intensity image; S4, mapping the feature points of the visible light image data to the point cloud data according to the 3D-2D coordinate mapping relationship. This solution can achieve a good image registration and fusion effect, can be applied to various platforms, and has a wide range of applicable scenarios. The second aspect of this application proposes a system for fusing laser point cloud and visible light image.

A method and device for vehicle camera autocalibration during vehicle travel for driver assistance systems and automated driving. A vehicle camera images a region of vehicle surroundings through a window. The method includes: providing a vehicle camera projection model including multiple extrinsic parameters, at least one intrinsic vehicle camera parameter and at least one window parameter; capturing a sequence of camera images during vehicle cornering; determining a curve type during the cornering; estimating the parameters using pixels in the sequence of images of stationary objects in the vehicle surroundings, the current vehicle movement, and the determined curve type, by minimizing an error function indicating the deviation between pixels which correspond to stationary objects in the vehicle surroundings and which are established from the sequence of images and pixels of the stationary objects which are projected by the projection model; and outputting at least one of the estimated parameters.

The present invention discloses a telecentric imaging combined with Scheimpflug projection three-dimensional microscopic measurement system and a joint calibration method, which establish a Scheimpflug projection model, a Scheimpflug distortion model and a telecentric imaging model; capture and preprocess the target attitude images of the calibration plate, perform the phase unwrapping of the center of the telecentric camera and the center mapping of the projector, estimate the internal parameter intrinsic matrix, the external parameter matrix and the distortion coefficient of the projector, correct the projector distortion and the Scheimpflug angle; optimize the error of the external parameter matrix of the projector; align the three-dimensional coordinates of the center of the calibration plate to the coordinate system of the projector, and calibrate the projection matrix of the telecentric imaging model; perform the camera-projector joint calibration to realize the calibration of the three-dimensional microscopic measurement system with high precision. The present invention can solve the problem of limited depth of field under small field of view and high magnification, overcome the reconstruction error caused by defocus of the projection and imaging branches, and increase the dynamic measurement range and accuracy.

The invention belongs to the technical field of image processing, and provides an image blurring correction method and device, electronic equipment and a medium, and the method comprises the steps: carrying out the projection of an image and a standard map based on a blurred image, building a Gaussian-Kruger projection model, and obtaining auxiliary parameters, calculating to obtain a horizontal coordinate and a vertical coordinate in a projection plane rectangular coordinate system based on the auxiliary parameters, converting the pixel points into coordinates of the plane rectangular coordinate system, marking the converted coordinates of the pixel points as converted coordinates, generating a sampling signal if the converted coordinates and the projection coordinates are inconsistent in the same plane rectangular coordinate system, and outputting the sampling signal. The method comprises the following steps: sampling a sampling signal, re-sampling an image by adopting a bilinear interpolation method based on the sampling signal, marking a pixel point as a deteriorated pixel point if the pixel value of the pixel point of the sampling image is smaller than the pixel value of the pixel point of an original image, obtaining a deteriorated performance value based on the deteriorated pixel point, obtaining error data based on an adjustment signal, and outputting the error data. And adjusting the deteriorated coordinates according to the error data.

The invention discloses a personalized emotion regulation system and method based on music therapy, and relates to the technical field of intelligent emotion intervention, and the method comprises the steps: collecting a real-time emotion index of a user based on an individual high-sensitivity emotion regulation time period, predicting an emotion perturbation index through a weighted time attenuation integral function, and recognizing a mild emotion fluctuation state of the user; constructing an embedded feature projection model, and generating an intervention music parameter set according to the mild emotion fluctuation state of the user; playing intervention music according to the intervention music parameter set, collecting feedback signals in real time, and calculating an intervention response score by constructing an intervention response score function; and constructing a historical intervention response data set based on the intervention data set, and generating an intervention music recommendation strategy through an intervention situation parameter mapping method. According to the method, an intervention music recommendation strategy is generated through an intervention situation parameter mapping method, and historical forward intervention samples are clustered into intervention response categories.

The invention discloses a belt conveyor coal flow detection method based on monocular vision, and the method comprises the steps: 1, setting a monocular camera which is used for collecting a conveying belt and a coal flow image, and determining the relation between internal and external parameters of the camera and a world coordinate system; 2, obtaining a coal flow foreground image; 3, feature point detection and description are carried out on the coal flow foreground image, and feature points are matched between adjacent frames to obtain matching points; 4, recovering the three-dimensional coordinates of the feature points by using the matching points and a monocular camera perspective projection model in combination with the motion information of the conveying belt, and obtaining the point cloud data of the surface of the coal flow; and 5, carrying out surface fitting on the point cloud data, and calculating the volume and mass flow of coal passing through a coal flow interface in unit time by calculating the sectional area of the coal flow and combining the movement speed of the conveyor belt. A binocular or multi-view vision system and an expensive and complex traditional metering device are not needed, and the system cost and the installation and maintenance difficulty are reduced.

The invention relates to an EOS-like three-dimensional data generation method, in particular to a method for generating EOS-like three-dimensional data through CT scanning data, a computer program product and terminal equipment, and solves the technical problem that an existing EOS-like three-dimensional data generation method is low in efficiency and precision. According to the method, a physical projection model based on EOS system geometric parameters is constructed, the geometric projection process of EOS system imaging is precisely restored, and a style migration network and a three-dimensional reconstruction network are established by means of deep learning; the style migration network realizes conversion from CT scanning data to biplanar EOS data by utilizing the view angle complementary characteristic of front and side projection; according to the three-dimensional reconstruction network, an adversarial learning architecture of double generators and double discriminators is utilized, and high fidelity of generated EOS-like three-dimensional data in geometric structure and texture details is ensured through collaborative optimization of adversarial training and cyclic consistency constraint. The matching of the style migration network and the three-dimensional reconstruction network can greatly improve the generation efficiency and precision of the EOS-like three-dimensional data.

The invention relates to the technical field of industrial Internet of Things and edge computing, in particular to an intelligent risk identification method and system for an energy increasing station. The method comprises the following steps: deploying a sensor network at an energy adding station and synchronously acquiring signals, extracting multi-scale time-frequency and physical response characteristics, mapping heterogeneous characteristics to energy flow fingerprints through a hybrid projection model, and performing self-calibration enhancement by using a differential baseline; energy flow fingerprints are decoded and mapped into semantic features, candidate abnormal modes are recognized through short-term trend analysis and multi-source cross correlation, and local abnormal scores are calculated; constructing a physical semantic constrained local causal network based on candidate anomalies, deducing an anomaly propagation path, quantifying node risk contribution, grading and positioning a key risk source; and packaging the risk information into a token matching strategy library, executing a transactional action chain according to a hierarchical intervention principle, monitoring an effect in real time and supporting rollback upgrading. According to the invention, real-time identification, causal deduction and intelligent dynamic response of the energy station risk are realized.

A method for generating a dynamically structured electronic file associated with a defined location. The method includes receiving health information from a covered entity computing system and a file generation request from a user computing device. The method further includes combining HCP information with the health information and determining multiple digitally projected values using at least one digital projection model. The method further includes generating the electronic file including at least one digitally projected value and at least a portion of the HCP location information. The electronic file is generated as the file type identified by the file generation request, and is structured based on at least one of the file generation request or the file destination.

A method for generating an electronic file includes generating a health information request and providing the health information request to one or more covered entity computing systems. The method further includes receiving health information and health care provider (HCP) information associated with multiple HCPs. The method further includes combining the health information with at least a portion of the HCP information to generate combined health information. The method further includes determining multiple digitally projected values based on the combined health information using one or more digital projection models. Each digitally projected value of the plurality of digitally projected values is associated with an HCP of the multiple HCPs. The method further includes generating the electronic file including at least one digitally projected value of the multiple digitally projected values. The method further includes providing the electronic file to a file destination address.

The invention discloses a map construction method and device based on point-line features, equipment and a medium, and the method comprises the steps: obtaining a current image frame corresponding to a target scene, inputting the current image frame into a lightweight point-line detection model, and obtaining point features and line features; determining whether the current image frame is a key frame according to the point features and the line features, and determining three-dimensional space points and three-dimensional space straight lines based on the point features and the line features when the current image frame is the key frame; optimizing the three-dimensional space point and the three-dimensional space straight line based on a space point error model and a space straight line projection model to obtain a target space point and a target space straight line; and constructing a three-dimensional space map corresponding to the target scene based on the target space point and the target space straight line. The precision and robustness in a structured scene are further improved while the positioning and mapping speed is ensured.

The embodiment of the invention provides an Internet of Vehicles beam prediction method and device based on a multi-modal large model. The method comprises the following steps: acquiring a camera image and positioning data of a target vehicle, a base station position of a road section and a three-dimensional map of the road section; inputting the positioning data, the position of the base station and the three-dimensional map of the road section into a ray tracing model to obtain propagation characteristics of a wireless communication signal; inputting the propagation characteristics and the camera image into a scatterer projection model to obtain scatterer characteristics in the image; and optimizing the multi-modal large model and constructing a scattering thermodynamic diagram according to a channel feature data set containing camera images and scatterer features, and further obtaining a beam prediction data set for beam prediction model training for training. According to the technical scheme, the channel characteristics in the camera image can be effectively extracted, the beam index and the beam coherence time in the codebook can be accurately predicted in combination with the channel characteristics and the positioning information, and the communication transmission rate and the energy efficiency of the system are improved.

The embodiment of the invention provides an MPV servicing vehicle body dynamic stiffness analysis method, device and equipment and a computer readable storage medium. The method comprises the following steps: acquiring a first system matrix of a reordered MPV servicing vehicle body and a reordered first external steady-state excitation vector; converting the first system matrix into a second system matrix through a constructed projection model; converting the first external steady-state excitation vector into a second external steady-state excitation vector based on the position of a non-zero element in the first external steady-state excitation vector; calculating a residual vector based on the second system matrix and a second external steady-state excitation vector; calculating a global residual vector based on the residual vector; based on the global residual vector, dynamic stiffness analysis of the MPV servicing vehicle body is completed, in this way, efficient scheduling and solving of large-scale residual vector tasks under hundreds of working conditions are achieved, and the overall calculation efficiency and the resource utilization rate of frequency response analysis are remarkably improved.

The invention relates to a cultural and creative product design display method and system based on augmented reality, and the method comprises the steps: obtaining design drawings of cultural and creative products, determining the projection relation between the design drawings according to the projection relation of the design drawings, and generating a three-dimensional projection model of the cultural and creative products for displaying the cultural and creative products in a display region; in the process of user-oriented display, the visual angle of the user is used as a rendering target of the three-dimensional projection model, so that the three-dimensional projection model is rendered only within the visual angle of the user. The immersive cultural and creative product display experience is provided for the user, the three-dimensional projection model of the cultural and creative product can be viewed from any angle, and the cognition and interest of the user on the product are greatly improved.

The invention discloses a highway engineering pavement quality measurement and calculation method based on a remote sensing technology, and particularly relates to the technical field of remote sensing measurement and calculation, and the method comprises the steps: fusing multi-modal remote sensing data, introducing a dynamic feature enhancement mechanism through a graph neural network, and generating an initial feature enhancement graph; correcting resolution and angle distortion in the initial feature enhancement image through a self-adaptive alignment mechanism, outputting a self-adaptive alignment feature image, separating vegetation occlusion and humidity interference in the self-adaptive alignment feature image, and generating a pavement feature optimization restoration image; the vegetation occlusion separation model constructs a 3D projection model of highway engineering pavement vegetation through multi-view vegetation projection reverse tracking, and shadow interference is eliminated; the humidity interference separation model decomposes low-frequency disturbance and high-frequency anomaly in thermal infrared temperature distribution through Fourier transform, eliminates humidity interference, and solves the problems of feature extraction distortion and low pavement quality measurement and calculation precision caused by vegetation occlusion and humidity interference.

The invention relates to the technical field of mechanical manufacturing and machining, in particular to a dressing wheel and honing wheel design method for improving contact line stability in the gear honing machining process. Based on workpiece gear parameters, a left and right tooth surface mathematical model is established, a honing process space coordinate conversion relation is established, a conjugate meshing relational expression is derived by combining the relative slip speed of meshing contact points and a normal vector, and a tooth surface contact line model is established; and the calculation modeling of the two-dimensional projection of the left and right tooth surface contact lines, the projection intersection point position and the variation under the same rotation angle is realized. And a honing wheel dressing contact line model under dressing wheels with different tooth numbers and a tooth surface contact line intersection projection model in the dressing and honing process under the tooth number difference are established. A honing wheel and variable tooth number dressing wheel design method is provided, and geometric and technological parameters of the honing wheel and the variable tooth number dressing wheel are determined; and a trimming and honing two-degree-of-freedom conjugate meshing relation and a modified tooth surface numerical model are constructed and verified, discretization and point cloud processing are conducted on the model, high-precision tooth surface point cloud is obtained, and accurate machining of a trimming wheel and a honing wheel is guided.

The invention relates to a method for monitoring a region of interest of a subterranean formation, the region of interest comprising a point of interest, the method comprising: extracting a first subset (1) of raw geophysical data associated with said point of interest from a set (0) of raw geophysical data previously acquired to generate a first image (Im1) of the subterranean formation; constructing a projection model (MOD1) on the basis of the first subset of data (1); reducing the first subset of data (1) to a second subset (2); creating a reference set (B) by applying the projection model (MOD1); performing the acquisition forming a third subset (3); creating a monitoring set (M) by applying the projection model (MOD1); comparing the first reference set (B) with the first monitoring set (M) in order to identify the evolution of the subsurface layer to be observed.

The invention relates to the technical field of simulation optimization, and discloses a charging module heat dissipation optimization method based on temperature field simulation, and the method comprises the steps: firstly discretizing a heat dissipation space into voxel units, and collecting flow heat data; calculating the flow resistance sensitivity according to the relationship between the flow velocity vector and the main wind direction; calculating an effective convection potential energy density and a gradient vector thereof by combining a Reynolds number and a temperature difference; then, generating a chasing cold source driving vector based on the heat flux demand of the component; establishing a thermal wake flow cone projection model, and calculating a thermal wake flow rejection vector; generating a flow resistance avoidance vector in combination with the regional flow velocity direction; and finally, performing weighted synthesis on the three vectors to obtain optimized displacement, and updating coordinates of the component. According to the technical scheme, through multi-physics field coupling analysis, while a driving component finds a high cooling potential area, flow channel smoothness and thermal wake avoidance are effectively considered, and deterministic optimization of the charging module layout is realized.

The application discloses a 4D video generation method fusing monocular vision and terrain elevation data, comprising the following steps: acquiring video frame images and corresponding camera pose data collected by a monocular camera; acquiring terrain elevation data of a target area, and constructing a three-dimensional elevation network model; based on the camera pose data, establishing a ray projection model for pixels in the video frame images, calculating the intersection of the rays and the three-dimensional grid model, and obtaining the reference distance from the monocular camera to the ground surface corresponding to the pixels; generating an initial relative depth map of the video frame images by using a depth estimation model; selecting high-confidence ground pixels from the video frame images as reference points, taking the reference distance corresponding to the reference points as the true value, and performing absolute scale correction on the initial relative depth map to obtain an absolute depth map; performing back projection calculation on the absolute depth map, the camera pose data and pixel color information to generate a three-dimensional point cloud, mapping the three-dimensional point cloud to a real geographic coordinate system, and generating 4D video data in time sequence.