10 results about "Edge orientation" patented technology

Methods, systems, and devices for an antenna subsystem are described. An antenna subsystem may include multiple printed wiring boards and multiple antenna substrates mounted on multiple sides of the printed wiring boards. The antenna substrates may include one or more planar-oriented elements that emit or receive in a planar orientation and one or more edge-oriented elements that emit or receive in an edge orientation. The various antenna elements may be connected to one or more analog-to-digital converters that may convert signals received at the antenna elements to obtain digital component receive signals that may be processed by one or more signal processors according to a set of beam weights to obtain a signal of a radio frequency beam that may have a field of view greater than (180) degrees.

The present invention discloses a method for fitting, analyzing, and assessing the complexity of road crack morphology. The method uses ground-penetrating radar to scan the road surface to obtain a grayscale image of the horizontal cross-section of the crack, and then uses a semantic segmentation method to obtain a binary image of the crack. The binary image of the horizontal cross-section of the road is obtained, and then an opening operation is used to filter noise, and a closing operation is used to connect the crack areas. Contour detection is also used to separate different crack areas and process them separately. After obtaining the preprocessed image, the crack area is downsampled to extract the crack area skeleton, and feature points are identified on the skeleton. The feature points are connected using a minimum spanning tree, and finally further simplified to obtain an undirected graph that can represent the road crack morphology. The edge orientation and node degree of the undirected graph are counted to determine the shape of the crack, and the complexity of the crack morphology is assessed by the complexity of the undirected graph. The present invention can be used to guide road maintenance personnel to handle crack diseases according to complexity priority.

The application discloses a kind of based on digital twinning turnout switch machine monitoring and fault diagnosis system and method, belong to rail transit field, including based on edge orientation and edge edge federal union's cloud edge collaborative mode to the data of turnout switch machine is collected and is governed;Establish turnout switch machine twinborn model, including three-dimensional model, behavior model and diagnostic model, and will switch machine work twinborn data integration and fusion in three-dimensional model, realize three-dimensional visualization;Based on one-dimensional power signal twinborn data and two-dimensional GASF image parallel learning fault diagnosis method diagnoses whether turnout switch machine fails.This application uses the above-mentioned based on digital twinning turnout switch machine monitoring and fault diagnosis system and method, effectively improve the switch machine operation and maintenance efficiency, reduce the operation and maintenance cost of switch machine, can be more intuitive, efficient, intelligently realize switch machine health management.

Embodiments are provided for stimulation of somatosensory cortex such that (i) the perceptions of force induced thereby exhibit increased levels of discrimination, allowed for finer-resolution perceptions to be achieved, (ii) perceptions of edges or other geometric aspects of objects can be delivered, and (iii) perceptions of motion of objects can be delivered. These embodiments include providing such stimulation to multiple electrodes or other stimulation sites synchronously, with the multiple stimulation sites evoking perceptions whose locations on the hand at least partially overlap. Perception of edges can be evoked by synchronously stimulating multiple stimulation sites somatotopically oriented along the orientation of the edge. Perception of motion can be evoked by providing sequential stimulus from one stimulation site to another, with the interval between sequential stimuli non-overlapping enough to induce perception of motion while close enough in time to evoke a single percept rather than a sequence of discrete percepts.

The invention relates to the technical field of medical image analysis and artificial intelligence crossing, in particular to a neurosurgery image diagnosis system based on graph recognition, which comprises an image preprocessing module, a graph feature extraction module, a multi-modal fusion module, a focus decision module and a nerve diagnosis positioning module. According to the method, the graph path network is constructed through the edge trend, the spatial continuation relation of the interruption contour between the faults and the connection structure direction is cut through, region stripping is performed on the offset structure between the modes, the boundary segments in the differentiated source image are divided into the corresponding coordinate blocks, the path interference of the overlapped and mixed region is avoided, and the accuracy of the differentiated source image is improved. After the structure path is extended, a continuous path in a graph layer is established between a lesion area and a functional axis domain, a control node is connected to a functional response boundary according to a direction trend, a positioning chain for lesion paths to lead to a nerve area is formed in the graph layer, and functional partitions are labeled and connected according to a connection path relation. Neuro-attribution ranges among the graph areas are integrally divided according to the structure trend.

The application relates to the field of artificial intelligence, and discloses a bus safety early warning method and system supporting road condition shadow removal, which comprises the following specific steps: acquiring an original image; inputting the original image into an HSI space and constructing a shadow identification index SI; obtaining a shadow preliminary detection image; obtaining a shadow image and a shadow preliminary removal image; performing intrinsic decomposition on the shadow preliminary detection image to obtain a color orientation template; constructing an edge contour verification image pair of the original image to obtain a structural skeleton as an edge orientation template; constructing a generative adversarial network; obtaining a detection result output by a discriminator based on the color orientation template and the edge orientation template; obtaining a road condition shadow removal image according to the detection result; and performing bus safety early warning according to the road condition shadow removal image. The application solves the problems that the existing bus safety early warning technology training depends on data, and the phenomena of fuzzy repair area, inconsistent chroma and boundary artifacts, and has the characteristics of high early warning accuracy.

This invention discloses an IoT fault diagnosis method and system based on dynamic causal graph learning. The method collects three types of heterogeneous data streams: network signaling, device telemetry, and platform logs, and performs type-aware standardization preprocessing to generate a standardized multimodal time-series matrix. It identifies subsets of changing variables and anomaly markers through sliding window statistical feature change detection. It performs local skeleton updates and edge orientation on the causal adjacency matrix using incremental mixed conditional independence testing, dynamically maintaining a causal directed acyclic graph. When an anomaly is detected, a candidate root cause set is constructed, and the average causal effect value of each candidate root cause is quantified using a do-intervention propagation algorithm based on a structural causal model. The root cause localization results are then sorted and output according to the average causal effect value. The system includes a multi-source heterogeneous data acquisition and preprocessing module, an anomaly detection and change subset identification module, a dynamic causal graph learning module, a counterfactual inference module, and a root cause report generation module.

The invention relates to the technical field of blind person perception assistance, in particular to a blind person image perception assistance system and method based on electric tactile sensation. The system comprises an image acquisition and basic processing module, a key object identification and mask generation module, an edge and gray information processing module, an edge-guided dynamic scanning module, a multi-mode electric tactile coding and output module and a user feedback adjustment module. The method comprises the following steps: acquiring an image, identifying a key object, extracting edge and gray information, dividing grids based on an edge trend, performing dynamic scanning, and finally mapping stimulation information to a hand and brain bimodal electric tactile array for output. According to the method, hand accurate contour touch and brain overall imaging stimulation are fused, a closed-loop adjustment mechanism based on key object recognition and user feedback is introduced, the problems that a traditional method is inaccurate in image structure perception and low in information transmission efficiency are effectively solved, and the perception efficiency and recognition accuracy of the blind to image information are remarkably improved.

The invention discloses a digital twinning-based turnout switch machine monitoring and fault diagnosis system and method, and belongs to the field of rail transit, and the method comprises the steps: carrying out the collection and treatment of the data of a turnout switch machine based on an edge guiding and edge-edge federation combined cloud edge cooperation mode; establishing a turnout switch machine twinborn model which comprises a three-dimensional model, a behavior model and a diagnosis model, and integrating and fusing switch machine twinborn data into the three-dimensional model to realize three-dimensional visualization; the fault diagnosis method based on one-dimensional power signal twinborn data and two-dimensional GASF image parallel learning is used for diagnosing whether the turnout switch machine breaks down or not. According to the turnout point switch monitoring and fault diagnosis system and method based on digital twinning, the operation and maintenance efficiency of the point switch is effectively improved, the operation and maintenance cost of the point switch is reduced, and health management of the point switch can be achieved more visually, efficiently and intelligently.

The application relates to the technical field of image processing, in particular to an image reconstruction method based on edge orientation constraint. A non-convex regularization term is constructed based on edge information of an image block, an L1-TV model is combined to construct an image reconstruction model, and a mature optimization algorithm is used for solving. The model uses dynamic edge detection to locate a key structure area of an image, and correspondingly protects wavelet coefficients, so as to reduce the shrinkage deviation of large coefficients, and thus edge and texture information can be more accurately reserved.