52 results about "Boundary detection" patented technology

The application discloses a time capsule expression structure reservation method based on deep learning and a knowledge graph, and aims at solving the problems that the expression and organization structure of a user's sealed multi-modal content in a digital time capsule service is difficult to be identified and recorded, and the display according to the uploading time or the fixed template of the media type in the opening stage is easy to cause the distortion of the expression intention and the fragmentation of the receiving experience. The multi-modal content input in the sealing stage is normalized and time-aligned, the content representation is obtained by using multi-modal hierarchical coding, the segmentation boundary and hierarchical relationship are determined and the key weight and object information are extracted by combining span boundary detection and a pointer network, the narrative rhythm parameters are obtained by using a neural time point process modeling based on a media switching event sequence, a timing knowledge graph is fused and constructed, and the arrangement sequence and the presentation control parameters are generated under the sequence constraint and the segmentation continuous constraint by graph representation learning, and the presentation data for the display in the opening stage is generated, so that the technical effects of reserving the user's expression structure and rhythm and differentially arranging and presenting in the future are realized.

The application discloses a kind of high-efficiency boundary detection methods based on angle entropy weighted spring network, it is related to image boundary detection technical field, the method includes: for each data point in data set, search its multiple near neighbors;Calculate the elasticity of each near neighbor to current data point, elasticity is based on Hooke's law simulates spring connection;The resultant force of all elasticities is calculated as basic boundary score;Calculate the angle entropy of current data point, angle entropy is based on the angle information of near neighbor distribution Quantification direction distribution;With angle entropy weighted basic boundary score to obtain final boundary score;Select boundary point by pre-set threshold, complete boundary detection.The application quantifies local stress imbalance by spring network, and utilizes angle entropy to amplify boundary feature, while ensuring linear time complexity, significantly improves the discrimination of boundary point detection.

This application discloses a method, apparatus, medium, and product for detecting lane boundaries, relating to the field of vehicle control technology. The method includes: acquiring image data of the vehicle's environment using a camera; and scanning point cloud data of the vehicle's environment using a lidar scanner; identifying lane boundaries in the image data to obtain pixel information of the lane boundaries in the image data, the pixel information including pixel positions; mapping the image data to the point cloud data to obtain fused point cloud data, the fused point cloud data indicating the mapping result of the lane boundary pixel information in the point cloud data; and based on the fused point cloud data, obtaining a distance value sequence corresponding to the lane boundary, the distance value sequence indicating the lane width. By acquiring environmental data of different dimensions, the stability and accuracy of boundary detection results under different driving environments are improved.

The application discloses a complex road boundary detection method and device based on point cloud voxel processing and belongs to the field of road detection. The method comprises the following steps: acquiring point cloud image data of articles around a road vehicle driving area, and performing voxel segmentation; adding a fixed point in the voxel to expand the voxel features; inputting a single-layer full connection layer to obtain a high-dimensional feature vector matrix; performing global feature transformation on all point cloud high-dimensional feature vector matrices in the voxel; selecting the global features corresponding to the k nearest point clouds as the center to aggregate; taking different values of k to obtain voxel features at different scales, and performing fusion; performing regression on the fused features to obtain related information of the articles around the vehicle driving area; calculating the boundary position of the vehicle driving area to obtain the width of the vehicle driving area, and determining whether the vehicle driving area is passable. The complex road boundary is accurately detected.

The application discloses a kind of video intelligent slice method based on multi-modal information fusion and semantic constraint, it is related to video content analysis and intelligent editing technical field, it is characterized in that it proposes semantic priority audiovisual collaborative slice scheme, obtains shot interval by shot boundary detection, constructs voice interval and effective word information by voice recognition, adopts voice interval as semantic mask to remove visual cut point in the process of voice expression, and based on fragment length and effective word, content density determination is carried out to long fragment, and further adopts visual re-cutting, audio energy driving and uniform cutting Secondary slicing strategy of division, the method provided by the application solves the problem of semantic fragmentation and content perception loss in the prior art, can obtain video fragment with complete semantics, high content density and appropriate length, and is suitable for various application scenarios such as automatic editing, short video generation and video content retrieval.

The application discloses a method and device for adjusting a drilling trajectory of a horizontal well. First, a standard well used for stratum comparison with a well to be drilled is determined, and a horizontal well geosteering model is established in combination with geological data and drilling engineering data. A current well resistivity while drilling and a while drilling gamma curve are compared with a standard well logging curve, and a target point vertical depth is calculated. In combination with a real-time response of a while drilling azimuthal resistivity boundary detection curve, a landing point of a target layer is determined, and a suitable hole inclination angle is used to enter the layer. A drilling trajectory and a relative position relationship with a stratum interface are determined by fitting a while drilling simulation curve of the horizontal well geosteering model with a current well actual drilling curve. A stratum interface azimuth and a distance from the trajectory to the interface are determined in real time by developing a while drilling azimuthal resistivity boundary detection rapid inversion, and the horizontal section drilling trajectory is adjusted. In combination with logging data and directional actual drilling characteristics, a layer position where the trajectory is located is judged, and a sand body distribution and a stratum change trend are predicted in combination with a regional seismic profile, so that the drilling trajectory is pre-adjusted.

The application relates to an AI-assisted large-scale lip language recognition data set automatic construction method, which comprises the following steps: S1: a distributed automatic crawler system is constructed to capture video materials; S2: the collected original video is preprocessed; S3: the video stream is subjected to shot boundary detection, different shot segments are segmented, and a pre-trained SyncNet model is used for audio and video synchronization alignment; S4: the audio stream is subjected to text recognition, and one-to-one correspondence between a sentence and an audio timestamp is realized to obtain a structured sentence-level subtitle data set; S5: an MTCNN algorithm is used for face detection, and the speaker in the video is subjected to identity distinction and clustering; S6: face detection data is obtained according to the MTCNN algorithm, lip key point data is obtained, and a corresponding region of interest (ROI) is extracted. The application effectively improves the construction efficiency and quality of the lip language data set.

The application relates to a model stealing attack query detection method for a machine learning-based network intrusion detection system and relates to the technical field of network attack detection.The application aims to solve the technical problem of combining query samples and model responses for comprehensive analysis, adopting a combination of decision boundary leakage evaluation and reconstruction error evaluation to quickly identify model stealing attacks with a small amount of query samples.The technical points are as follows: the prediction results of the query samples are used to construct a cumulative distribution function, the model uncertainty is measured, and potential boundary detection behaviors are detected; the reconstruction error loss of the query samples is calculated by using an automatic encoder, potential abnormal queries deviating from the normal distribution but not showing obvious malicious characteristics are identified; based on the results of the decision boundary leakage evaluation and the reconstruction error evaluation, a model safety coefficient is calculated to comprehensively evaluate the possibility of whether the model is subjected to a model stealing attack in a set period of time.The application is suitable for scenes where the ML-NIDS needs to be quickly detected and real-timely defended.

This invention provides a vehicle control device. The vehicle control device includes a moving object detection unit, a boundary detection unit, and a control unit. The moving object detection unit detects moving objects present near the vehicle. The boundary detection unit detects the boundary between the lane in which the vehicle is traveling and a road adjacent to, but outside, the lane. When the moving object detection unit detects a moving object on the road, the control unit executes at least one of the following control modes based on the detection result of the boundary detection unit: offset control to move the vehicle away from the boundary in the vehicle width direction, deceleration control to reduce the vehicle's speed, and notification control to send a notification. The control unit switches control parameters for the control mode based on the boundary height of the boundary between the vehicle and the moving object in the vehicle width direction.

This invention discloses a method for constructing a semantic segmentation neural network model for riverbank collapse monitoring scenarios. The method includes: training a teacher network containing dual-path convolution and dynamic masking mechanisms using a riverbank collapse image dataset, introducing geometric consistency loss during training to strengthen boundary features; extracting collaborative correlation features from the teacher network that represent the structured dependencies between boundary detection and region segmentation tasks; constructing a single-branch lightweight student network, and using a distillation loss function containing alignment terms of collaborative correlation features to guide student network training. This invention eliminates background redundancy through dynamic sparse computation and transfers prior knowledge from the dual-task approach to the single-task network through function-attribution-guided collaborative distillation, solving the problems of fuzzy boundary detection and high inference latency at the edge of the model, thus achieving high-precision, low-power real-time monitoring.

This application provides a control method for a surface cleaning device, belonging to the field of cleaning robot technology. The method includes: if the surface cleaning device climbs onto a first leaking object during the execution of the first boundary detection action, then during the execution of the return task, the surface cleaning device travels a first distance along a first direction from the X-coordinate of the ending position to the X-coordinate of the stopping position; the first distance is the absolute value of the difference between the sum of the first displacement and the sum of the second displacement. The control method for the surface cleaning device provided by this application has the advantages of being able to return to a position near the initial position and being convenient for the user to retrieve.

This invention relates to the field of computer technology, specifically to a method, apparatus, electronic device, and computer-readable medium for allocating decoration resources. One specific embodiment of the method includes: performing spatial entity topology construction processing on building information to obtain a set of room entity component information and a set of component topology information; performing combination construction processing on the set of room entity component information to obtain a set of component combination feature information; based on the component topology information set, performing room function identification processing on the component combination feature information set to obtain a set of room function labels; performing material boundary detection processing on the set of room entity component information to obtain a set of boundary feature information; performing process material parsing processing on the set of room function labels and the set of boundary feature information to obtain a set of process material information; and generating decoration resource allocation instructions based on the process material information set to control decoration resource allocation equipment to execute decoration resource allocation. This embodiment improves the adaptability of decoration resource allocation.

The embodiment of the specification discloses a data processing method and device for labeling and cleaning cooperation and medium, relates to the technical field of data processing, and the method comprises the following steps: obtaining an original data set, extracting semantic features in the original data set, marking the original data set, and generating labeled guided thermal data; input the labeled guided thermal data into a labeling node, real-time collect the labeling behavior interaction data of the target user of the labeling node in the labeled guided thermal data, the labeling behavior interaction data includes operation data coordinate sequence and coordinate correction sequence; based on the labeling behavior interaction data, identify the semantic suspicious area, so as to detect the entity boundary of the semantic suspicious area through the cleaning node, and generate the corresponding semantic level cleaning suggestion; according to the semantic level cleaning suggestion, the labeling of the semantic suspicious area is corrected, the labeling information corresponding to the original data set is determined, and according to the semantic level cleaning suggestion, the data cleaning rule is optimized, so as to realize data cleaning.

This invention discloses a semantic point cloud boundary extraction and vectorization method based on multimodal fusion, aiming to solve the problems of low boundary extraction accuracy, poor adaptability to complex scenes, and lack of structured output in existing technologies. The method comprises five stages: multimodal boundary confidence modeling, fusing semantic uncertainty, geometric abrupt changes, and probabilistic gradient features to generate confidence scores; adaptive segmentation and type classification, automatically classifying boundary types; graph neural network boundary connection optimization, repairing breaks and removing noise; structured polyline generation and curve optimization, obtaining smooth vector boundaries; and trajectory-guided priority sorting, outputting a priority-based structured boundary list. This invention improves boundary detection accuracy and robustness, outputs vector boundaries conforming to high-precision map standards, and is suitable for scenarios such as autonomous driving and intelligent robot navigation, demonstrating strong engineering practicality.

The application belongs to the field of industrial safety monitoring, and discloses a foreign matter border crossing detection method, computer equipment and a storage medium. The method comprises the following steps: acquiring a current video frame; inputting the current video frame into a warning line segmentation model and a foreign matter detection model respectively to determine a binary mask of the current video frame and a dynamic detection frame for foreign matter; determining at least one warning boundary point set of the current video frame based on the binary mask; performing linear regression fitting on each warning boundary point set to obtain a corresponding candidate fitting warning line, and generating a corresponding candidate warning area based on each candidate fitting warning line; selecting a target warning area with the highest overlap degree with a current calibration warning area from each candidate warning area; if the overlap degree is less than a preset threshold, regarding the target warning area as a new calibration warning area; and determining whether there is foreign matter border crossing in the current video frame based on the dynamic detection frame and the new calibration warning area. The application can improve the accuracy of foreign matter border crossing detection.

This invention discloses an intelligent data analysis method for cognitive care in elderly care information service systems, relating to the field of smart elderly care health monitoring technology. The method includes extracting a mixed dynamic monitoring data stream of elderly behavior and physiology, and separating it into time-series queues according to the source. Event boundary detection is performed on the behavioral activity data to identify the start and end points of independent activity units. Based on this, synchronized data segments are extracted from the physiological data queue and paired to generate a comprehensive snapshot data package of activity status. After consistency verification, the set of valid data packages is input into an adaptive analysis frequency scheduler to obtain a real-time updated demand scanning time interval. This interval is used to periodically traverse the data package set and extract features to generate a structured service demand feature vector. Finally, a specific elderly care service project suggestion instruction is output through an online service pattern matching engine. This invention achieves accurate data synchronization and on-demand adaptive intelligent analysis and scheduling centered on activity events.

The present disclosure provides a road boundary detection method, a classification model generation method and device, and relates to the technical field of intelligent driving. First, a first point cloud frame currently collected by a millimeter wave radar is obtained, and then feature points in the first point cloud frame are preprocessed to obtain point cloud data to be identified. Then, the point cloud data to be identified is input into a preset classification model to obtain a classification label corresponding to each feature point output by the classification model. Finally, the current road boundary is determined according to the feature points with the corresponding classification label for the road boundary. Thus, the influence of the road environment on the road boundary detection is effectively avoided, and the accuracy and reliability of the road boundary detection method are improved.

The application discloses a kind of texture mapping methods suitable for indoor furniture three-dimensional model based on semantic boundary perception, including edge enhanced point cloud sampling, semantic boundary detection, bidirectional texture parameterization mapping and structure feature supervision etc. steps.The method is first carried out structure sensitive sampling to three-dimensional grid by dihedral angle analysis, to improve the point cloud density of edge and high curvature area;Subsequently, the semantic segmentation result is calculated and the dihedral angle is screened according to the threshold value, and the semantic boundary point corresponding to the fabric piece area splicing seam, edge rolling bar etc. position is identified, and it is used as the basis for texture joint optimization.Adopt bidirectional network structure of forward texture mapping and inverse three-dimensional reconstruction to generate texture UV coordinate, and combined with conformal loss, stretching loss, boundary loss, smoothness loss, clustering loss and consistency loss are optimized jointly, to improve the parameterized geometric fidelity and structure continuity.The application further constructs columnar feature detection module.

This invention discloses a method for detecting algebraic confusion characteristics and anti-attack boundaries of cryptographic systems based on topological homology invariants, belonging to the field of cryptographic security technology. The aim is to address the technical problems of existing anti-attack capability detection methods, which rely on empirical testing, cannot quantify algebraic structure characteristics, and cannot predict security boundaries. The method includes: constructing a chain complex topological model of the algebraic structure of the cryptographic system; numerically solving for the homology group and the topological invariant Betti number; determining algebraic confusion characteristics and anti-attack capabilities based on the Betti number; scanning and locating critical points of the anti-attack boundary; and hierarchical triggering of early warning and adaptive structural optimization. This invention provides an independent and controllable quantitative evaluation scheme for compliance testing of national cryptographic algorithms, enabling early prediction and closed-loop protection of the anti-attack boundary of cryptographic systems. It can be modularly embedded into domestic cryptographic testing platforms, adapting to various scenarios such as national cryptographic algorithms and post-quantum cryptography, and has strong engineering applicability.

This invention discloses a method, device, equipment, and storage medium for geometric correction of hidden road defects based on mechanical drive. The method includes: constructing a finite element simulation sample library for road defects; extracting and fusing multidimensional features from the sample library to obtain a fused feature vector; using this vector to construct a dataset for training to obtain a proxy model for defect parameter inversion; locating abnormal areas of the road medium using 3D ground-penetrating radar and activating the corresponding strain sensor array; acquiring measured strain data and fusing it into a feature vector to be identified; inputting this vector into the proxy model for inversion; and outputting the geometric parameters of hidden road defects. This effectively combines the advantages of 3D ground-penetrating radar and strain sensor arrays, compensating for the shortcomings of single detection methods, and effectively supplementing the inaccuracy of ground-penetrating radar in detecting the boundaries of hidden defects. Through multidimensional feature extraction and fusion and neural network model training, the deep information of strain data is accurately mined, improving the estimation accuracy of geometric parameters of hidden road defects.

The application provides a water body boundary identification method and device based on boundary perception collaborative optimization, belongs to the field of artificial intelligence remote sensing SAR image segmentation, and comprises the following steps: a deep learning model is constructed, a real-time double-branch semantic segmentation framework is adopted to meet the timeliness requirement of water body boundary identification; an auxiliary boundary prediction branch is introduced to highlight high-frequency semantic information, a boundary detection is taken as an optimization target, and a boundary perception loss is introduced to predict complex water body boundaries; a pixel attention module, a context fast aggregation module and a boundary attention guiding module are proposed to mine spatial detail information, context information and boundary information of a target image respectively, control effective learning of context semantic information, guarantee reliability and timeliness of extracted information, guide effective fusion of various information at a boundary area, jointly optimize original double-branch and auxiliary branches, and realize accurate identification of water body boundaries. The application can improve identification precision.

This application provides a method and apparatus for entity recognition of scientific and technological achievement application texts and for constructing a knowledge graph. The method includes: acquiring the text of the scientific and technological achievement application to be recognized; inputting the preprocessed text into a pre-trained entity recognition model; performing compound nesting boundary detection on the text and dynamically dividing the text into semantic units; extracting the bidirectional dependency graph convolution features of each semantic unit; capturing the multi-head dynamic local features of each semantic unit based on the bidirectional dependency graph convolution features and the multi-head dynamic local features; performing state transition based on a gated hierarchical state transition mechanism according to the bidirectional dependency graph convolution features and the multi-head dynamic local features of each semantic unit, generating a state vector word by word and decoding entity labels, and outputting a structured entity sequence corresponding to the scientific and technological achievement application text. This application can improve the accuracy and precision of entity recognition of scientific and technological achievement application texts, thereby ensuring the accuracy of knowledge graph construction.

A system and method for imaging, for example, using intravascular ultrasound (IVUS) imaging devices, with components and accessories, for example, catheters, catheter interface modules, stands, workstations, tablets, displays, and carts. The components can be controlled or interacted with through hands-free commands, voice control, gestures, and can be augmented with artificial intelligence and / or machine learning. Real-time measurements and border detection with enhanced imaging are provided.

This invention discloses an optical dual-modal imaging device for detecting the boundary of thalamic gliomas, belonging to the field of optical imaging. The device includes an optical coherence elastography (OCE) subsystem and a hyperspectral imaging (HSI) subsystem. The OCE subsystem acquires the mechanical properties and three-dimensional tomographic structural information of the tissue; the HSI subsystem determines the location of the thalamic glioma over a large area and acquires biochemical information. The two subsystems are coupled optically via a dichroic mirror and share a scanning galvanometer and scanning lens to ensure spatial matching of the detection area. A temporal collaborative scanning mode is employed, where the HSI subsystem first performs a large-scale scan to locate the abnormal area, and then the OCE subsystem performs precise elastic and structural imaging of that area. This invention overcomes the limitations of single imaging technologies through dual-modal functional complementarity, achieving high-resolution and accurate detection and imaging of the infiltration boundary of thalamic gliomas.

This invention provides a low-altitude airspace monitoring method and beacon terminal system based on multi-protocol fusion, relating to the fields of low-altitude airspace monitoring, the Internet of Things, and communication scheduling. The method involves parsing the original positioning statement and battery voltage information to obtain positioning data and battery percentage data; filtering the positioning data to obtain noise-reduced trajectory data and flight trajectory records; performing boundary detection on the noise-reduced trajectory data and no-fly zone boundary data to obtain boundary judgment results; processing the noise-reduced trajectory data and preset flight path data to obtain collision avoidance interception judgment results and yaw markers, thereby obtaining flight compliance review results; and processing the flight trajectory records, flight compliance review results, and battery percentage data to obtain continuously active flight status display data and alarm trigger signals. This invention solves the problems of poor reliability, large positioning deviation, easy locking under high-concurrency read / write operations, and low efficiency of compliance review calculations in existing low-altitude airspace monitoring systems.

An apparatus includes processor circuitry configured to communicate with an intravascular imaging catheter. The processor circuitry is configured to output a first screen display to a display in communication with the processor circuitry, the first screen display including an intravascular image obtained by the intravascular imaging catheter, wherein the intravascular image includes a vascular lumen and vascular tissue. The processor circuitry is further configured to: receive a single user input on the intravascular image identifying a location within a region of interest; and automatically determine the boundary of the region of interest in response to the single user input, wherein the boundary surrounds the location identified by the single user input. The processor circuitry is further configured to output a second screen display to the display, the second screen display including the intravascular image and the boundary of the region of interest superimposed on the intravascular image.

This invention discloses a method, device, and computer-readable storage medium for acquiring physical limit data of a joystick. The method is applied to a joystick module with boundary detection functionality. The joystick module is equipped with a sensor component that outputs a limit trigger signal when the joystick cap deflects to its maximum physical travel. The acquisition method includes: in response to the limit trigger signal, acquiring the logical coordinate values ​​of the joystick component; calculating the deflection angle of the joystick component and the corresponding physical limit modulus based on the logical coordinate values; and updating the joystick physical boundary data set with the deflection angle and the physical limit modulus as physical limit data. This invention eliminates the data lag and deformation blind spots caused by purely software-estimated boundaries, providing an absolutely reliable and dynamically evolving underlying data foundation for adaptive output calibration throughout the joystick's entire lifecycle.