163 results about "Spatial maps" patented technology

The invention relates to a few-sample image classification method based on hyperbolic space image-text local feature alignment, and belongs to the technical field of image recognition and artificial intelligence, and the method comprises the steps: generating word-level attribute description for a support set image through employing a multi-mode large language model; encoding the image and the text by adopting a vision-language model; constructing a hyperbolic local feature alignment module in a hyperbolic space, screening most relevant image local features for text local features by calculating hyperbolic cosine similarity, and fusing by using hyperbolic weighted average; designing a hyperbolic cross attention module, and aggregating key information from the multi-modal local features of the support set to construct a category prototype by taking query image aggregation features as guidance; and finally performing classification based on the hyperbolic geodesic distance. According to the method, the hierarchical modeling capability of the hyperbolic space and the semantic priori knowledge of the large language model are fully utilized, fine-grained multi-modal feature alignment is realized, and the small sample image classification performance is improved.

The invention discloses a mangrove forest distribution information extraction method based on deep learning and remote sensing images, and the method comprises the steps: firstly, constructing a spatial diagram fusing ecological priori knowledge such as hydrological connectivity, and extracting high-dimensional features containing a complex space-time dependence relation from an irregular satellite image time sequence through employing a PG-STGT network; a physical information guided antagonism decoupling mechanism is subsequently adopted to explicitly decompose the high-dimensional feature into three subspaces. And finally, according to the method, a high-robustness distribution diagram is generated by applying the decoupled identity feature vectors, and a multi-dimensional mangrove forest health index is generated by using residual error abnormal features. According to the method, the physical mechanism and deep learning are deeply fused, the time consistency of the classification result is improved, and the ability of diagnosing the health condition of the ecological system is provided.

The invention discloses a spatio-temporal feature fusion modeling method for multi-source sensing data, and relates to the technical field of data processing, and the method comprises the steps: obtaining multi-source original spatio-temporal data of a sensor, including densely distributed data and sparse dotted data; for the dense distribution data, extracting statistical distribution characteristics of the process state data, calculating an operation entropy and an operation temperature, and generating regional dynamic characteristic data; for sparse point data, extracting space and time sequence statistical characteristics of environment parameters, calculating environment difference degree and environment stability, and generating regional environment characteristic data; generating target spatio-temporal feature data based on unified spatio-temporal granularity alignment, asynchronous missing detection and dynamic interpolation; modeling is carried out through a time sequence branch, a space map branch and a cross-source fusion branch, and a prediction result is output; the sensing accuracy and the prediction reliability of the industrial operation environment coupling system are improved by introducing the dynamic characteristics and the environment characteristics.

The invention relates to the technical field of AGV intelligent control, and discloses an AGV intelligent control method and system based on end-cloud collaboration, and the method comprises the steps: obtaining the position, obstacle and environment data of an AGV in real time, constructing a dynamic space map, carrying out the grid processing, and when the channel width is detected to be not enough for safe passing, carrying out the grid processing of the dynamic space map; the method comprises the following steps: firstly, adopting an A * algorithm to quickly generate an alternative path, then carrying out multi-AGV cooperative conflict detection through path overlapping comparison, carrying out global optimization on a scheduling sequence and a passing priority of multiple AGVs by applying a genetic algorithm, and finally generating a conflict-free efficient scheduling instruction. According to the method, through multi-algorithm fusion and a real-time decision-making mechanism, the passing efficiency and the space resource utilization rate of multiple AGVs in a dynamic environment are improved.

The invention relates to the technical field of water quality monitoring, and discloses a sewage quality on-line monitoring method and system.The sewage quality on-line monitoring method comprises the steps that time alignment processing and data quality evaluation are conducted on original water quality sequences collected at all monitoring point positions, and aligned data and data quality weights are obtained; constructing a time delay space diagram; performing joint estimation on the global water quality state to obtain global state estimation and uncertainty; performing anomaly detection and identifying an abnormal propagation path and a suspected source to obtain an anomaly score and a source confidence sorting list; formulating a self-adaptive sampling strategy, and determining the sampling frequency of each monitoring point position; on the basis of the time-delay observation equation and weighted optimization, online joint estimation of the global water quality hidden state is achieved, reverse traceability is carried out by combining the residual standardization anomaly score and the time-delay space diagram, the anomaly can be found, the possible source and propagation direction of the anomaly can be located, and the pertinence and interpretability of disposal are improved.

The invention relates to a bridge crane operation attitude control method and a control system, which are used for accurately hoisting a heavy object in a narrow space, and the method comprises the following steps: obtaining operation area space constraint information to generate a space map, and determining a hoisting path and a path width; planning a driving track of the driving mechanism along the central line of the path, marking direction switching nodes, and calculating the walking distance of each straight line segment; determining an allowable maximum swing range according to the width of the lower-section path; a speed control scheme is formulated according to the walking distance and the swing space, and it is ensured that weight swing does not exceed the limit during direction switching. By actively planning the swing space and intelligently adjusting the motion parameters, the hoisting efficiency is remarkably improved while the safety is guaranteed.

A robotic device scans at least a portion of an environment. The robotic device includes one or more LiDAR sensors to scan the environment. A management system receives sensor data generated by the one or more LiDAR sensors to determine a three dimensional (3D) point cloud representing at least the portion of the environment. A layout of the environment is determined, where the layout represents a location of objects within the environment. At least one discrepancy between the 3D spatial map and the layout is determined. Based at least in part on at least one discrepancy, a map of the environment is generated.

In various examples, embodiments are directed to identifying map data (e.g., relevant to a route) using a quad-tree spatial index. In this regard, spatial map data that indicates various map features is represented in a quad-tree spatial index for use in identifying map data. To identify map data, bounding shapes may be generated in association with various segments of a route. An indication of an object-oriented bounding shape may be used to query the quad-tree spatial index to identify map data related to the object-oriented bounding shape. In embodiments, an object-oriented spatial index may be generated that indexes the object-oriented bounding shapes associated with the route. The object-oriented spatial index may be used to query the quad-tree spatial index to identify map data related to the corresponding object-oriented bounding shapes. Alternatively, the quad-tree spatial index may be used to query the object-oriented spatial index to identify map data.

The invention relates to the technical field of intelligent transportation, and particularly discloses a site selection optimization method and system for a temporarily-built plant station of a highland mountainous area expressway. The method comprises the following steps: acquiring functions of a concrete mixing station, a precast beam field and a temporarily-built plant station of a steel bar processing plant to obtain a BIM risk simulation program; acquiring a plateau mountainous area live-action three-dimensional model, and fusing the plateau mountainous area live-action three-dimensional model with a BIM risk Acquiring geological and climate data, converting the geological and climate data into a GIS space map layer, and associating the GIS space map layer with a BIM risk simulation program; a built-in geological taboo rule is set, rasterizing scanning is automatically carried out on the whole domain, and a high-risk area is eliminated; dangerous source identification is carried out on terrain risks, climate risks and construction interaction risks; according to the identification risk type and grade, recommending a protection structure and generating a BIM component; and automatically generating a plurality of site selection coordinates and a plant station layout optimization scheme. According to the method, the period of traditional site selection and protection design is shortened, and meanwhile the scientificity and economical efficiency of the scheme are guaranteed.

Systems and methods for generating high-resolution spatial maps of microbiome and physicochemical indices for an agriculture site are provided. The spatial maps are generated from a limited / reduced number of physical samples acquired using a smart sampling tool provided by the systems and methods described. Insights for the agriculture site can be used to guide selection and application of interventions, according to various intervention archetypes, based upon the customized needs of the agriculture site. Performance of the agriculture site can thus be enhanced in an unprecedented, accessible, and sustainable manner.

The invention discloses a crowdsourcing digital information trace leaving system and method for an augmented reality environment, and relates to the technical field of augmented reality, the system comprises a client device and a cloud server, and data interaction is carried out between the client device and the cloud server; wherein the client equipment comprises an environment sensing module, a positioning module and a digital nick processing module; the cloud server comprises a map index module, a digital nicking module, a management module and an operation calculation module; the environment sensing module senses the environment and its own position based on a sensor. Professional team acquisition is replaced by a crowdsourcing mode, construction and dynamic extension of a global high-precision AR space map are realized at extremely low cost, and the core pain point of industry high-cost mapping is solved; the four interaction media cover discrete information marking-spatio-temporal backtracking-3D creation-2D anchoring of a whole scene, deep binding of digital information and a physical space is achieved, unprecedented AR social immersion is provided, and a sustainable profit mode is provided for a platform.

The invention provides a building information model and city information model cross-scale consistency three-dimensional modeling method based on space intelligence. The method comprises the following steps: extracting a three-dimensional geometric patch set from an original building information model, constructing an initial modeling object and a component space diagram, and calculating a transformation operator through footprint matching to realize automatic alignment; the user-defined family attributes are analyzed to execute cross-scale semantic mapping, semantic classification information is generated, and a building shell model is generated through geometric generalization processing; opening features are extracted and mapped to the shell model, three-dimensional topology reconstruction is executed in combination with the component space diagram, and city information model target components with topology closing performance are generated. And finally, performing incremental updating based on the alignment deviation. According to the method, the problems of inaccurate geographic alignment, geometric degradation and semantic loss in cross-scale model fusion are solved, and the logic leakproofness and data maintenance efficiency of urban digital twin base modeling are effectively improved.

In one aspect, a device management platform is provided. The device management platform includes environmental sensors and a host system. The environmental sensors are deployed at different locations within a gaming venue, each including at least one sensor configured to capture environmental data at one of the different locations. The host system is configured to receive, from the environmental sensors, the environmental data, identify spatial data that defines a floor layout of the gaming venue and the different locations of the environmental sensors, correlate the spatial data with the environmental data to generate a spatial map of the environmental data within the gaming venue, and identify a subscriber for the spatial map. The host system is further configured to determine, based on the subscriber, access rules for the spatial map, and provide, based on the access rules, at least a portion of the spatial map to the subscriber.

The invention relates to the technical field of urban thermal environment assessment and ecological space optimization, and discloses an earth surface heat island intensity assessment method, system and device and a storage medium, and the method comprises the steps: obtaining blue-green landscape fragmentation results under different window scales; determining an optimal threshold window for blue-green landscape fragmentation measurement; calculating the foreground area density of the blue-green landscape in the research area under the optimal threshold window; based on the foreground area density, carrying out fragmentation type division on the blue-green landscape to generate a blue-green landscape fragmentation type spatial distribution diagram; acquiring ground surface heat island intensity data of the research area in different time periods, and performing spatial matching with the blue-green landscape fragmentation type spatial distribution diagram; and constructing a comprehensive evaluation model. According to the method, the defects that a traditional landscape index result is abstract and is greatly influenced by unit division, and functional forms cannot be distinguished are overcome, and an intuitive and operable space map basis is provided for thermal environment regulation and control.

The invention discloses a transformer substation multi-source heterogeneous data processing method and system based on space layer superposition, and relates to the technical field of electric power data processing, and the method comprises the steps: classifying the multi-source heterogeneous data of a transformer substation based on a data structure type, and obtaining a plurality of category data sets; pre-processing the plurality of category data sets to obtain a plurality of pre-processed category data sets, and storing the pre-processed category data sets in different domains; establishing a unified model based on equipment common attributes of the transformer substation, and embedding the plurality of preprocessed category data sets into a bottom geographic distribution map based on the unified model; the bottom geographic distribution map comprises a plurality of space map layers, and each space map layer corresponds to one data type; and performing dynamic coupling on the plurality of space layers, and constructing a three-dimensional fusion model with a space-time correlation characteristic. According to the method, the technical problems of long time consumption and weak spatial dimension analysis capability of spatial correlation analysis of multi-source heterogeneous data in the prior art are solved.

This invention discloses an artificial intelligence-based method and system for visualizing urban planning, belonging to the field of data processing technology. The method includes: acquiring multi-source heterogeneous urban basic data and planning schemes to be evaluated; constructing a heterogeneous attribute spatial map through temporal denoising and feature matching; using the planning scheme as a priori excitation condition, inputting it along with the map into a multi-layer spatiotemporal perception graph neural network model with topology preservation loss, and outputting a spatiotemporal evolution prediction matrix tensor; constructing an adaptive weighted grid evaluation model based on multi-dimensional constraints such as perspective, predicted polarization gradient, and hardware load, and combining it with PID closed-loop monitoring of dynamic threshold, to reconstruct a high-efficiency urban visualization 3D chassis model with weighted allocation in real time. This invention effectively solves the problems of false connectivity distortion in traditional topology prediction and computational power collapse caused by rigid LOD distance pruning, achieving deep collaboration between highly realistic situational evolution and adaptive computational power.

This invention discloses an AI-interactive AR (Augmented Reality) cultural wall system for cultural tourism, belonging to the field of AR system technology. The surface of the cultural wall is equipped with a pre-embedded feature set, including visual markers, differentiated texture features, 3D depth variation areas, and specifically designed interactive hotspots. These features provide the system with stable visual benchmarks, semantic distinction criteria, depth cues, and precise positioning anchors. The system includes: a feature point acquisition module, used to collect the feature set on the cultural wall through a multimodal feature extraction algorithm to construct a 3D spatial map with semantic annotations; a user positioning and pose estimation module; an AI content generation engine; and a spatial adaptation and rendering module. Through the cultural wall feature set and the multi-module collaborative system, precise spatial integration of virtual content and the physical wall surface is achieved, along with intelligent dynamic content generation based on user behavior, effectively enhancing the immersion, interactivity, and personalization of the AR cultural experience.

The invention relates to a biodiversity charting method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining remote sensing observation data, foundation observation data and species information data, constructing an ecological data cube, extracting statistical features, frequency features and phenological features according to the ecological data cube, and calculating the statistical features, the frequency features and the phenological features according to the statistical features, the frequency features and the phenological features; the method comprises the following steps: constructing a species diversity space map, a phylogenetic diversity map and a global genetic diversity map, fusing the maps to obtain a fusion result, identifying a high-diversity region and a low-protection region according to the fusion result, and evaluating the high-diversity region and the low-protection region to obtain an evaluation result. Therefore, the problems that related technologies depend on the number of samples and data precision, phylogenetic and genetic layer patterns are difficult to reveal, and global scale decision and management requirements are difficult to meet are solved, multi-source satellite remote sensing and foundation data can be fused, and the comprehensiveness and scientificity of diversity evaluation are improved.

The invention provides an AI-based text generation method and system, and the method comprises the steps: extracting a global semantic text vector sequence from text data, and extracting a spatial correlation image vector sequence from image data; obtaining a text and image attention weight matrix and an image and text attention weight matrix based on the two; further acquiring a global text and graph vector sequence and a spatial text and graph vector sequence, and acquiring multi-modal fusion features based on the global text and graph vector sequence and the spatial text and graph vector sequence; and taking the multi-modal fusion features as condition information of a language model, outputting a plurality of query texts through the language model, and outputting confidence coefficients corresponding to the query texts. Through fine-grained alignment, the relevance between image-text features is ensured, the problem of modal difference is solved, and the semantic relevance between different modals is improved; the dependency degree on texts or images in the image-text fusion process is dynamically calculated based on the gating weight, and deep semantic association between different modes is further mined.

The application relates to the field of surveying and mapping, in particular to a laser-IMU installation deviation calibration method, a surveying and mapping method and a system based on visual assistance, wherein a plurality of images under a plurality of laser radar calibration conditions are processed according to camera parameters and camera-IMU correlation parameters, laser radar-IMU installation deviation is obtained, manual operation is avoided, high-precision and high-efficiency deviation calibration is realized, the relative spatial relationship of the laser radar-IMU is adjusted according to the laser radar-IMU installation deviation, the accurate matching and installation of the laser radar and the IMU are ensured, the frame corresponding relationship between the IMU data and the point cloud data is constructed according to the dynamic characteristics of a surveying and mapping path, the most matched point cloud data points of each IMU data position point on the surveying and mapping path are screened, a local point cloud map corresponding to the position point is constructed, and therefore the spatial map of a target region where the surveying and mapping path is located is integrated and constructed. The application can reduce data omission and improve the accuracy and reliability of spatial surveying and positioning through local point cloud data processing and map construction.

The embodiment of the invention relates to equipment, a method, a device and a medium related to spatial map layering. In one aspect, a first device sends a request message associated with a subscription to a spatial map to a second device, where the request message includes first hierarchical information indicating at least one layer of the spatial map. The first device receives a response message from the second device, the response message including a layer list associated with the subscription to the spatial map and second hierarchical information for the layer list. A layer list associated with the subscription is determined based on at least one layer indicated by the first layer information. By implementing the embodiments of the present disclosure, a hierarchical structure for a spatial map is introduced, thereby enabling more dynamic and flexible representation and management of a virtual environment.

This application discloses an AOI matching method based on spatial context awareness and adaptive multimodal feature fusion, comprising: extracting geometric and textual features from AOIs from two different map platforms; constructing a heterogeneous spatial map; using a heterogeneous graph Transformer model to perform context aggregation and feature updates on the heterogeneous spatial map to obtain the spatial context embedding features of the AOI; constructing a global spatial context vector of the AOI, and obtaining multimodal refined features through a GRU gating fusion mechanism; fusing the multimodal refined features through an intra-source attention mechanism to obtain intra-source embedding features, and performing bidirectional cross-attention calculation through a cross-source attention mechanism to obtain the inter-source embedding features of each of the two map platforms; and determining the AOI matching probability based on the inter-source embedding features and the spatial embedding vectors of candidate AOI pairs. This method solves the problem of poor AOI matching performance under special data such as missing names and coarse contours, and in complex heterogeneous scenarios, thereby improving the matching accuracy of AOIs.

The invention discloses a robot control method and device, and belongs to the technical field of electrical equipment. The method comprises the steps that in the process that the mechanical arm is about to execute or execute a specified action, first space map information around a machine body is obtained, and second space map information needed by the mechanical arm for executing the specified action is obtained; wherein the second space map information comprises the space map information required by the mechanical arm for executing the specified action in a barrier-free manner; and the first space map information and the second space map information are compared to obtain a comparison result, and the mechanical arm is controlled to execute or not execute the specified action based on the comparison result. Whether the first space map information meets the requirement that the mechanical arm executes the specified action or not can be compared according to the first space map information and the second space map information, so that the mechanical arm can be prevented from colliding with an obstacle in the process of executing the specified action, and the mechanical arm can execute the specified action in different scenes to avoid the obstacle; and therefore, the use safety of the mechanical arm is improved.

The invention relates to the technical field of bioinformatics and deep learning, and discloses a space gene expression enhancement method based on multi-modal deep learning. According to the method, a three-branch feature extraction module is constructed, a target point scale branch module extracts local detail features, a neighborhood branch module strengthens the representation capability of a spatial context, and a global branch module provides macroscopic organization structure information, so that the problem of insufficient information under a single view angle is effectively solved through combination of the three branch feature extraction modules; on this basis, a linear Transform encoder is introduced to perform efficient modeling on different scale features, and deep information fusion is performed through a multi-head cross attention mechanism, so that the model can accurately capture spatial correlation between different regions; and a high-resolution interpolation strategy is introduced in a data construction level, so that the continuity and the fine-grained expression capability of the spatial atlas are remarkably improved.

This invention relates to the field of forestry resource monitoring technology, and discloses a dynamic monitoring system and method for forestry resources based on remote sensing imagery. The system includes: generating temporal remote sensing reflectance data within the same grid; generating a continuous canopy occupancy map; generating an infill set; determining the intrinsic neck scale; calculating the topological spectrum intensity of the continuous canopy infill; calculating the interlayer decoupling topological index; generating monitoring judgment results; and outputting change patches. This invention constructs an adaptive multi-scale erosion sequence based on the intrinsic neck scale, combines Eulerian features to quantify the infill topological fragmentation process, and integrates the degree of infill fragmentation with the stability state of the outer envelope through the interlayer decoupling topological index. This achieves accurate determination of change units and precise spatial patch location, avoiding the omissions or misjudgments of deep forest understory structure changes by traditional techniques, ensuring that the monitoring results accurately reflect the actual mechanisms of dynamic changes in forest resources.

In an augmented reality (AR) experience, virtual content may be rendered at a particular position within a 3D spatial map and overlaid onto a view of the real-world space. There may be scenarios in which the user wants to limit a 3D model to being rendered within a particular subspace of the space defined by the 3D spatial map. Computer-implemented methods are disclosed that include receiving input defining a subspace of a 3D spatial map of a real-world space. A set of 3D models may then be filtered to identify a subset of the 3D models that fit within the subspace defined by the input. AR content including a render of a particular 3D model from the subset and overlaid onto a view of the real-world space in a position within the subspace may be output for display.

Systems, methods, and compositions for generating a spatial map of a distribution of targets of a sample are described. Systems, methods, and devices for generating a spatial map of a distribution of targets of a sample on a substrate are described. A system for mapping targets can include a substrate; and a distribution of functionalized features associated with the substrate, wherein a representative feature of the distribution of functionalized features comprises: one or more functionalized molecules coupled to the representative feature, the one or more molecules including at least: a handshake sequence comprising a reactive portion, a barcode segment serving as a spatial address, and a cleavable linker configured to allow the handshake sequence to be released from the representative feature in response to a stimulus. The system can be used to tag nuclei, cells, and / or other target components of a sample.

The application discloses a kind of national regional geological mapping data organization retrieval method and system, the method includes: user initiates data query request from client;Parsing data query request, obtains search constraint condition;According to the search constraint condition, carry out first-level search in the associated information table of business database, determine all relevant project number, sheet number;According to the search constraint condition, carry out secondary search in the attribute information table of business database, retrieve all the attribute records of relevant sheet under the search condition;According to regional geological mapping data type, the search results are grouped, and the search results of the same type regional geological mapping data are merged into a search result set;Search result is returned to client, and visualized display is carried out in the form of space figure.The application has the advantages that: simple to realize, not only meet the efficiency requirement of data retrieval, but also provide the whole-process tracing ability from project planning to data application.

This invention discloses a deep learning-based method for detecting and tracking small unmanned aerial vehicles (UAVs). The method includes: 1) acquiring historical motion video data of the small UAV; 2) inputting the video into a salient target detection network to learn the UAV's features; 3) modeling the UAV's temporal and spatial maps using the features and position information of the same UAV at different times; 4) inputting the spatiotemporal maps into a trajectory tracking network based on long short-term memory (LSM) recurrent neural networks to track the UAV's trajectory; and 5) performing distance error analysis based on the tracked UAV trajectory. This invention provides a novel and practical method for tracking the motion trajectory of small UAVs. By using a salient target detection network to obtain the UAV's spatiotemporal information from historical motion videos, and by using a LSM recurrent neural network to model the UAV's trajectory features in both time and space dimensions, it achieves accurate detection and tracking of the small UAV's motion.