240 results about "Distance based" patented technology

The invention relates to a multi-modal perception fusion target following method and system. The method comprises the following steps: adopting an improved KCF algorithm to realize a closed-loop process of target tracking, multi-scale space construction, feature fusion, response calculation, optimal scale decision and model updating; designing a four-level shielding processing mechanism fusing motion prediction and depth verification, and realizing tracking recovery in a shielding scene through shielding judgment, motion prediction, fine search and template protection; constructing a target distance mapping function fusing geometric distortion correction and attitude compensation, and realizing high-precision distance estimation based on monocular vision; laser radar point cloud information is integrated, an obstacle threat degree model is constructed, and cooperative path planning of following and obstacle avoidance is realized in combination with an improved TEB algorithm; and designing a linear velocity control law and an angular velocity control law based on the distance deviation and the azimuth angle deviation, and driving the robot to complete target following motion. According to the invention, high-precision and robust following of the robot to the target can be realized.

The invention discloses an efficient frequency domain enhanced traffic sign detection method suitable for a snowy city scene, and belongs to the technical field of computer vision and intelligent traffic. According to the efficient frequency domain enhanced traffic sign detection method suitable for the snowy city scene, by designing a frequency domain compensation enhancement module, capture and fusion of multi-scale frequency domain information are achieved, and therefore the feature representation capacity and the model generalization performance are improved. According to the method, the YOLOv5 is used as a basic model for construction, the OfficientViT is used as a backbone network for feature extraction, the problem that the feature representation ability and generalization of a traditional model in snowy days are reduced is solved through a different-frequency feature complementation method, and meanwhile a loss function is optimized based on the Wasserstein distance and the thought of Gaussian reweighting. According to the method, different frequency features can be effectively complemented and enhanced, the feature representation capability in a snowy day scene is improved, and the provided FENet has good effectiveness and robustness in snowy day traffic sign detection.

The invention discloses a multi-modal large model reasoning acceleration method based on token variation discarding, and relates to the field of computer vision and artificial intelligence. The method comprises the following steps of: firstly, identifying an inert token with relatively small change amplitude by analyzing representation change of a visual token among layers of a large language model; secondly, designing a token variation measurement module based on an L2 distance, and quantifying the importance degree of each visual token; besides, a progressive discarding strategy is adopted, the visual tokens with low variation are gradually removed from a plurality of preset levels, and the problem of position deviation is avoided; and finally, by reserving a key visual token with high variation, the calculation complexity is remarkably reduced while the model performance is maintained, and the reasoning speed is increased. The method is completely compatible with a high-efficiency attention mechanism, does not need extra attention weight calculation, is mainly applied to the fields of intelligent question answering, video understanding, multi-modal content generation and the like, and has a wide application prospect.

The invention discloses a business question answering method and device, equipment and a storage medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining source domain and target domain data sets corresponding to new and old businesses of an electric power business hall, and extracting subsets to form a differential training set; determining a semantic association distance based on the difference between the vocabulary feature vector and the word vector, and obtaining a clustering cluster semantic association difference analysis value in combination with the similarity between the inter-cluster vocabulary semantic association distance and the text topic vector after the word is clustered; the vocabulary topic distribution conditions of different data set clustering clusters and the analysis values are fused, and the overall semantic feature values of the vth topic of the source domain and the kth topic of the target domain are calculated; determining attention weight and establishing a matrix, and generating a migrated intelligent language model by combining the two types of data sets; and answering can be obtained by inputting the questioning service text. The method can improve the accuracy of the output reply of the intelligent language model.

The invention provides a cable-type temperature-sensing fire detection method and system with an intelligent positioning function, and relates to the technical field of artificial intelligence, and the method comprises the steps: laying an optical fiber temperature-sensing cable along a preset path, obtaining the real-time three-dimensional coordinates of a temperature measurement point through employing a reflective mark point and a multi-view three-dimensional reconstruction technology, enabling the temperature data to be correlated with the coordinates to form a temperature field data set, and obtaining a temperature field data set; and generating three-dimensional temperature field grid data by adopting a weight optimization method based on distance attenuation, and giving temperature early warning and positioning information according to the three-dimensional temperature field grid data. According to the invention, accurate positioning and real-time early warning of temperature abnormity at the early stage of the fire disaster are realized, and the accuracy and response speed of fire disaster monitoring are improved.

The invention discloses an incomplete multi-mode smooth contrast clustering method based on information interpolation, which comprises the following steps of: firstly, modeling a missing view into multivariate Gaussian distribution based on distance weighted nearest neighbor by utilizing a view interpolation mechanism based on statistical information, and carrying out interpolation on the missing view to obtain a complete multi-view data set; secondly, using an encoder to extract potential features, capturing global structure information of multiple views through an FFN-Attention-FFN structure, and extracting local structure information of the multiple views through a graph convolutional network; thirdly, reconstructing a view by using a graph decoder; and finally, generating a clustering distribution result by using the MLP. According to the method, a view interpolation mechanism based on statistical information is introduced, the influence of a weak correlation view on a completion result is reduced by introducing distance weighting, and the data recovery quality is improved; the FFN-Attention-FFN structure is combined with the graph convolutional network, so that the global and local structure information of the data can be effectively captured; and negative sample pairs are expanded by adding Gaussian noise, so that sample distribution is smoother.

Systems and methods are disclosed for identifying relationships between complex datasets and / or high-dimensional datasets for predictive modeling. The method includes clustering data associated with one or more entities in a first dataset based on distance data; clustering the data associated with the one or more entities in a second dataset based on longitudinal data; consolidating the first dataset and the second dataset into a third dataset based on weights assigned to one or more edges between one or more nodes in the first dataset and the second dataset; generating a diagnosis space indicating a condition of the one or more entities based on the third dataset; and determining, via input of the diagnosis space into a machine learning model, an optimization of a weighting scheme for assigning weights to one or more features within the longitudinal data.

The invention discloses an incremental sample screening method for power grid transient stability discrimination model training. The method comprises the steps of obtaining a basic sample set based on a plurality of initial operation modes of a power grid; obtaining a to-be-selected sample based on the generated power grid operation mode; calculating the distance between the to-be-selected sample and each basic sample in the basic sample set; constructing a neighbor sample subset of the to-be-selected sample based on the distance; calculating a neighbor distance between the to-be-selected sample and the neighbor sample subset; judging whether the to-be-selected sample is an incremental sample based on the neighbor distance; and training the power grid transient stability discrimination model by adopting the incremental sample. The screening of the incremental samples only depends on time domain simulation and distance calculation, the identification difficulty of the incremental samples can be greatly reduced, and the data requirement of the artificial intelligence model training for the transient stability discrimination of the power grid can be effectively reduced by identifying the key samples with important value for stability discrimination.

A smart mirror system is provided, comprising a mirror, a camera, and a processor in communication with the camera and the mirror. In use, an image of a face is received for performing facial recognition. Based on the facial recognition, at least one of a plurality of users of the mirror is identified, for tailoring operation of the mirror for the at least one user.

The invention provides a virtual model generation method and device, electronic equipment, a computer readable storage medium and a computer program product. The method comprises the steps of determining description information for generating a virtual model in response to a received generation instruction of the virtual model, and generating a grid model based on the description information; determining a distance field set corresponding to the grid model, and performing structure sensing alignment processing on the grid model based on the distance field set to obtain a first model, the first model comprising a plurality of first geometric primitives; determining a first distance field subset corresponding to each first geometric primitive from the distance field set, and trimming the first model based on each first distance field subset to obtain a second model; and determining a plurality of target components based on the second model, constructing a target model based on the plurality of target components, and outputting the target model. According to the method and the device, efficient generation and accurate optimization of the virtual model can be realized, so that the quality and the efficiency of model generation are improved.

The invention discloses an intelligent blind person walking stick based on artificial intelligence, and relates to the field of intelligent walking sticks, and the intelligent blind person walking stick comprises a sensing module used for collecting environmental physical information in the advancing direction of a user in real time, and a processing module used for receiving multi-source environmental information collected by the sensing module, establishing a dynamic three-dimensional space model of the current local environment by taking a landing point at the bottom end of the walking stick as a current origin of coordinates; when the user touches the walking stick to the ground once, a'drop point event 'is triggered once, the three-dimensional space model is updated based on new drop point data, and the space offset between the current drop point and the previous drop point is calculated, including the moving distance and the direction change; compared with a scheme only based on distance perception or fixed path navigation, the method has higher environment understanding capability, navigation adaptive capability and real-time correction capability.

Techniques for matching security recommendation tasks with a regulatory compliance standard are disclosed. A regulatory compliance standard is received as input at a first Machine Learning (ML) model. Security recommendation tasks are received as input at the first ML model. A distance matrix defining a threshold of alignment that specifies a distance between the security recommendation tasks and the regulatory compliance standard is determined by the first ML model. Based on the distance matrix, identifying a predetermined number N of the security recommendation tasks that are within the threshold of alignment. A prompt including the predetermined number N of the security recommendation tasks and the regulatory compliance standard is generated. The prompt is inputted to a second ML model. Based on the prompt, the second ML model identifies a subset of the predetermined number N of the security recommendation tasks that match the regulatory compliance standard.

This disclosure provides a method and apparatus for estimating the latitude and longitude of a base station. The method includes acquiring measurement and statistical MR data of multiple cells covered by the base station to be estimated. The MR data includes at least one of the following: the identifier of the base station to be estimated, the received reference signal strength (RSRP), and the timing advance (TA). The MR data is preprocessed to obtain a set of MR sample points for the base station to be estimated. Based on RSRP or TA, a distance calculation model and an objective function are established. The distance calculation model is used to calculate the distance between the multiple MR sample points and the base station to be estimated. Based on the distance calculation model and the objective function, a gradient descent algorithm is used to determine the longitude and latitude of the base station to be estimated. This method reduces the amount of data required for solving the problem by preprocessing the MR data to obtain the set of MR sample points. The gradient descent algorithm is used to iteratively solve the objective function to obtain the longitude and latitude of the base station to be estimated, improving the speed of calculating the latitude and longitude of the base station and the accuracy of the measurement results.

The application belongs to the technical field of load identification of structural health monitoring, and provides a concentrated load positioning method based on principal stress constraint and strain gradient trajectory identification, which comprises the following steps: arranging strain sensors in a monitoring area of a planar structure plate and collecting strain data of measuring points, constructing a strain field inversion function based on a radial basis function and establishing an error optimization function containing a fitting error term and a smooth constraint, introducing a principal stress direction constraint and a gradient projection smooth constraint to form a comprehensive error function and solving to obtain an optimal strain field distribution, then calculating strain gradient vectors of each grid node and tracking a gradient trajectory through a gradient descent method, and finally performing an iterative clustering analysis based on distance statistics on a trajectory end point to output a cluster center as a concentrated load application position identification result. The application can improve the concentrated load positioning accuracy, enhance the anti-noise capability, and realize fast, stable and large-sample-free load position identification.

In the motion state detection method and self-moving cleaning device disclosed in this invention, when the self-moving cleaning device determines that it has moved a certain distance based on internal parameters, if the distance measurement value detects a small change in the relative distance between the self-moving cleaning device and objects in the environment, and the data state at this time matches the data state when slipping occurs, it can be directly determined that slipping has occurred. By combining the original hardware configuration of the self-moving cleaning device with relevant data statistics, it is possible to determine whether slipping has occurred. The hardware and software costs for slipping detection are extremely low, and the detection results are accurate. Even self-moving cleaning devices with lower hardware configurations can achieve slipping detection through software upgrades; without increasing purchase costs, users of self-moving cleaning devices with lower hardware configurations can also enjoy a good user experience.

The application discloses a kind of attention mechanism trajectory generation and simulation methods for sparse data completion, belong to intelligent transportation and trajectory prediction field.The application fills in trajectory missing value using high-precision sensor and map information, combines graph attention network (GAT) and multi-modal fusion technology;Adopt the attention module based on distance (D-GAT) and based on view (V-GAT), capture the interaction between vehicles, improve the understanding of complex traffic scene;Through prediction supervision generator and multi-modal trajectory generator, combine LSTM and Gaussian mixture model (GMM) to generate multiple possible trajectories, and use Kalman filter for online adjustment, ensure the accuracy and real-time of trajectory.The application realizes the intelligent completion of sparse traffic data and the accurate generation of trajectory, provides reliable data support and decision basis for intelligent transportation system, helps the efficient operation and sustainable development of urban traffic planning and management.

Embodiments of the present application provide a field of view angle range correction method, computer equipment and a storage medium. The method comprises: obtaining a target point cloud; determining a target inter-plate distance based on the target point cloud; obtaining a second point cloud set, determining a candidate inter-plate distance based on each frame of point cloud in the second point cloud set; and determining a target driving parameter based on the candidate inter-plate distance and the target inter-plate distance. The target point cloud obtained by the embodiments of the present application suppresses the point cloud distortion caused by the wide-angle lens, which is conducive to obtaining a reliable and accurate target inter-plate distance. The target inter-plate distance is used as a quantitative target for adjusting the driving parameter, and the driving parameter is constantly adjusted to obtain a target driving parameter that can make the candidate inter-plate distance consistent with the target inter-plate distance. The laser radar can drive the galvanometer to scan through the wide-angle lens at the target field of view angle range based on the target driving parameter. Therefore, the embodiments of the present application can help the laser radar to accurately and reliably output the laser line corresponding to the target field of view angle range.

This invention provides a cable-based temperature-sensing fire detection method and system with intelligent positioning function, relating to the field of artificial intelligence technology. It includes deploying fiber optic temperature-sensing cables along a preset path, acquiring real-time three-dimensional coordinates of temperature measurement points using reflective markers and multi-view 3D reconstruction technology, correlating temperature data with coordinates to form a temperature field dataset, generating a three-dimensional temperature field grid data using a distance-attenuation-based weight optimization method, and providing temperature warnings and location information accordingly. This invention achieves accurate location and real-time warning of early-stage temperature anomalies in fires, improving the accuracy and response speed of fire monitoring.

The application relates to the technical field of artificial intelligence and Internet of Things, and provides an Internet of Things model training method, device and equipment and medium based on zero sample learning, which can establish a feature vector space system comprising multi-dimensional features such as device attribute features, core data features and auxiliary features, and further improve the features in combination with artificial labeling and machine learning automatic labeling, utilize a preset convolutional neural network to establish a unified Internet of Things scene recognition model to assist in scene recognition of to-be-processed data, utilize distance based on a semantic space data feature vector to verify relevance, further check a scene recognition result, and when the verification is passed, train an Internet of Things model according to the recognized scene data, thereby solving the modeling problem of an Internet of Things scene lacking samples.

The invention relates to an intelligent detection method and system for the right-turning behavior of a large truck, and the method comprises the steps: extracting the positioning data of three key track points before, during and after turning distributed according to a time sequence in the right-turning process of the truck, and combining the fence information of a geographic information system; multi-dimensional feature vectors including speed, time, distance, direction and space area are constructed; spatial discrimination characteristics based on a distance threshold value and a region position are innovatively proposed, and four-level classification discrimination is performed according to the distance and the region attribution by calculating the distance and the relative position relation between a vehicle track point and a geo-fence. Through feature optimization processing and classification model training, three-classification prediction of vehicle parking behaviors is realized: direct passing, slow driving and parking. According to the invention, the right-turning parking behavior of the large truck can be accurately identified in real time, and an effective technical means is provided for traffic safety supervision.

This invention relates to the field of mining area traffic planning and discloses a method for planning vehicle speed in mining areas that integrates AI algorithms and multimodal data. The method includes the following steps: S1, determining that the current vehicle is in a following state and collecting the current vehicle's driving parameters, the position of the leading vehicle, and the distance between the two vehicles; S2, based on the positions of the current vehicle and the leading vehicle, determining whether the leading vehicle is traveling on a slope or about to leave the slope; S3, if the leading vehicle is on a slope or about to leave the slope, determining a safe following distance based on the distance between the two vehicles and the leading vehicle's slope travel distance; S4, planning the current vehicle's driving speed. This invention identifies vehicle following patterns and collects multimodal data in real time and comprehensively. It utilizes AI algorithms to perform high-precision perception and forward-looking prediction of the leading vehicle's slope travel status, enabling the solution to fully understand the complex terrain environment currently and in the future, thus allowing for pre-emptive risk assessment.

The invention discloses a plastic pipe extrusion on-line ovality detection and correction method and device, and belongs to the technical field of plastic pipe forming. Comprising the following steps: S1, pipe surface data measurement: driving a turntable to rotate around a pipe, and synchronously measuring distance and temperature through a displacement sensor and a temperature sensor on the turntable; s2, ellipticity calculation: calculating the real-time ellipticity and the distribution orientation of the pipe based on the distance data; s3, temperature partition calculation: calculating the average temperature and the temperature difference of each fan-shaped partition of the pipe based on the temperature data; and S4, ellipticity closed-loop regulation and control: associating the distribution orientation of the ellipticity with the temperature parameters of the corresponding subareas, and differentially adjusting the cooling parameters of the corresponding subareas on the setting machine so as to actively correct the ellipticity. According to the method, the ellipticity and the circumferential temperature are measured synchronously on line, and partition regulation and control are implemented based on'temperature-deformation 'association, so that closed-loop quality control from passive detection to active prevention is realized.

A system for navigation store, in a time-based buffer, a first set of frames acquired by a sensor; stores, in a distance-based buffer, a second set of frames acquired by the sensor; performs moving object segmentation on the first set of frames and the second set of frames to identify at least one moving object in a scene of the frames; predicts a trajectory of the at least one moving object; and performs a navigation function based on the predicted trajectory.

This invention relates to the field of quadruped robot navigation technology and discloses an intelligent navigation system for quadruped robots that combines behavior tree and visual recognition. The system includes modules for path processing, turn prediction, behavior tree decision-making, obstruction judgment, visual recognition and language evaluation, and navigation decision-making. The path processing module integrates multi-sensor data to acquire pose and gait state; the turn prediction module calculates safe turning speed and trigger distance based on a gait phase sliding window; the behavior tree decision-making module dynamically adjusts node priorities according to trigger intensity, and the switching timing is controlled by a gait phase arbiter; the obstruction judgment module generates path obstruction flags; the visual recognition module adopts a two-level architecture, calling a visual language model to evaluate the landing area for static traversable obstacles; and the navigation decision-making module integrates landing semantic confidence and outputs commands to cross, detour, wait, or return. This invention enables quadruped robots to achieve proactive predictive navigation and intelligent obstacle avoidance decision-making in complex industrial environments.

A method for measuring an inter-vehicle distance includes acquiring driving image photographed by a photographing device of a first vehicle which is being driven; detecting a second vehicle from the acquired driving image; detecting first feature points of a second vehicle region in a first frame corresponding to a frame in which the second frame is detected before a frame in which the second vehicle is not detected among a plurality of frames constituting the driving image, when the second vehicle is not detected from the driving image; detecting second feature points in a second frame corresponding to a current frame by tracking the detected first feature points; calculating a feature point change value between the first feature points and the second feature points; and calculating an inter-vehicle distance from the photographing device of the first vehicle to the second vehicle based on the calculated feature point change value.

Systems and methods are described for distance-based user interfaces. A distance between a user and a display can be determined. The distance between the user and the display can be determined based on a signal strength of a signal from a remote control. The distance between the user and the display can be determined based on audio signals received by a control device. A user interface can be modified based on the determined distance.

The invention provides a complex curved surface forming deviation evaluation method and system based on equidistant mapping, and the method comprises the steps: extracting the boundaries of a measurement point cloud and a standard point cloud, and carrying out the rough registration of the point clouds with the respective boundaries as reference; constructing an adjacent graph for each of the original high-dimensional measurement point cloud and the standard point cloud; calculating a geodesic distance based on the adjacent graph, and obtaining a shortest path matrix; mapping the shortest path matrix to a low-dimensional space at equal intervals, and expanding curved surfaces of the measurement point cloud and the standard point cloud to obtain a plane point cloud; fine registration is carried out by using the plane point clouds expanded by the measurement point cloud and the target point cloud; and comparing the measurement point cloud subjected to fine registration with the target point cloud to obtain a deviation cloud picture. According to the point cloud registration based on equidistant mapping, the deviation between the measurement point cloud and the standard digital model can be efficiently and accurately evaluated, and reliable data support is provided for secondary processing technology planning. And the method is particularly suitable for the integral wall plate with weak-texture variable-curvature molded surface characteristics.

A machine-learning based (ML-based) system and method for automatically extracting one or more data fields from one or more documents, are disclosed. The ML-based system includes a document obtaining subsystem to obtain documents, a document pre-processing subsystem to generate pre-processed data, a field identifying subsystem to identify data fields using a trained ML model, and a field extracting subsystem to extract financial information. The ML-based system also comprises an output subsystem to deliver the extracted data to end users via user interfaces. The ML model is trained using historical documents, labelled data fields, and features such as distance-based features, direction-based features, dimension-based features, positional features, and value-based features. The M-based system employs hyperparameter optimization, noise removal, and accuracy assessment mechanisms to enhance performance. This ML-based system provides a scalable, accurate, and automated solution for financial information extraction, ensuring efficiency, adaptability, and seamless integration with enterprise systems.

The invention provides an IPv6 (Internet Protocol Version 6) routing information base management method based on a geographic position and related equipment. The method comprises the following steps: converting prefix parts of all routing information into integer prefix intervals to obtain an initial routing information base; forming initialized aggregated data based on the initial routing information base, the distance information matrix and the current non-aggregated interval set; performing iterative aggregation on the prefix interval of the initial routing information base based on the distance information matrix to obtain an aggregation prefix interval and a corresponding aggregation position; updating the current non-aggregation interval set and the distance information matrix based on the aggregation prefix interval and the corresponding aggregation position; detecting whether a conflict interval exists in the current non-aggregation interval set or not; and in response to the situation that the current non-aggregation interval set does not have the conflict interval or has a single conflict interval but the conflict interval is different from the prefix interval in the current non-aggregation interval set, updating the initial routing information base based on the aggregation prefix interval and the corresponding aggregation position to obtain an aggregation routing information base.