526 results about "Visual presentation" patented technology

A system and a method for automatically discovering and managing actions in an application is disclosed. The system includes a data ingestion layer for receiving application data from multiple sources, a scanning and systematic traversal engine for interacting with UI elements and capturing network calls, an action mapping and generation module for correlating UI actions with API calls and categorizing actions, an AI-driven icon and description generator for creating visual representations and textual descriptions of actions, a user interface for displaying and modifying discovered actions, and a continuous monitoring component for triggering re-scanning based on coverage metrics, error detection, or version updates. The system employs synthetic data generation and AI-driven exploration to uncover hidden or undocumented APIs, enabling comprehensive mapping of an application's capabilities at the API level.

The invention discloses a language learning assistance application system based on speech recognition, and belongs to the technical field of learning assistance. The system comprises an intelligent voice acquisition and enhancement module for realizing acquisition and preprocessing of high-quality voice signals in a complex environment; the multi-modal feature extraction module dynamically extracts and fuses multi-dimensional learning feature information, completes feature analysis and boundary segmentation of a phoneme level, and is responsible for feature normalization and optimization; the deep speech recognition module is used for realizing high-precision speech recognition based on the normalized features; the intelligent evaluation engine module is used for realizing real-time and multi-dimensional evaluation on the language performance of the learner; the personalized learning management module integrates the evaluation results for dynamically planning an optimal learning path for the learner, manages the learning progress, and provides learning effect prediction and intervention suggestions at the same time; and the learning interaction experience module is responsible for visual presentation of learning feedback, multi-modal man-machine interaction design and user interface optimization.

The invention discloses a metal structural part surface damage identification method based on machine vision, and belongs to the field of machine vision, and the method comprises the steps: obtaining reference image data with known damage features, carrying out the preprocessing, analyzing the change trend of a system detection state, and judging whether there is a deviation correction demand or not. And if the deviation exists, carrying out geometric correction processing on the lens distortion error to obtain a corrected reference image. Further separating the real change of the damage from the system deviation, and combining low-resolution and high-resolution detection to obtain the distribution data of the suspected damage area and the specific characteristic parameter data of the damage. According to the method, quantitative data of damage levels are obtained through automatic classification, detection differences among multiple devices are calibrated, visual presentation information of damage positions and levels is generated, and finally camera parameters and algorithm thresholds for subsequent detection are optimized and adjusted, so that high-precision damage detection and evaluation are realized.

The invention relates to the technical field of artificial intelligence, and particularly provides an enterprise risk comprehensive assessment method and device, and the method comprises the following steps: S1, obtaining enterprise related risk information from a multi-source heterogeneous data source; s2, performing cleaning, standardization and feature extraction on the collected original data so as to adapt to subsequent model training and analysis requirements; s3, performing automatic risk identification and classification labeling on the preprocessed enterprise multi-dimensional data; s4, carrying out risk conduction analysis from single enterprise risks to an industrial chain, a region and even a whole economic system by constructing an enterprise association map and quantifying a risk infection mechanism; s5, performing multi-dimensional aggregation analysis and visual presentation on the enterprise risk; s6, performing dynamic monitoring and future trend prediction on enterprise risks; and S7, a user interaction module realizes understandability and verifiability of a risk assessment result. Compared with the prior art, the business efficiency can be improved, the financial risk can be reduced, and the healthy development of the financial market is promoted.

The invention relates to the technical field of artificial intelligence, and discloses a professional knowledge question and answer intelligent customer service system based on a self-optimization mechanism. The system comprises a user intention analysis module, a knowledge processing module, a self-optimization learning module and an interactive presentation module. A semantic understanding unit of the user intention analysis module generates a user intention signal; after the knowledge processing module receives the signal, a knowledge retrieval unit outputs related knowledge fragments and confidence, an answer generation unit forms candidate answers, and a quality evaluation unit determines an optimal answer according to the confidence; in the self-optimization learning module, a feedback analysis unit adjusts answer generation parameters according to user interaction data, a strategy adjustment unit optimizes a retrieval strategy in combination with an optimal answer and a historical dialogue, and a knowledge updating unit updates a knowledge base depending on an external knowledge source; and a multi-round dialogue management unit of the interactive presentation module adjusts a dialogue process, and a visual presentation unit outputs a natural language text and collects user feedback to a feedback analysis unit.

The invention discloses a multi-modal data fusion-based intelligent management system for a thoracic surgery monitoring unit, belongs to the technical field of medical information and artificial intelligence, and aims to solve the limitation of an existing thoracic surgery monitoring system in the aspects of multi-modal data fusion, heterogeneous data semantic alignment and intelligent deep analysis and prediction decision. The system is characterized by comprising a multi-modal data acquisition unit, a heterogeneous data fusion and semantic alignment module, an intelligent analysis and prediction decision module, a man-machine interaction and visual presentation module and a secure storage and management module. By the adoption of the technical scheme, comprehensive multi-modal data fusion, high real-time performance, deep intelligent analysis and prospective prediction can be achieved, intelligent decision support, resource optimization, continuous learning and self-adaptive optimization are provided, and the intelligent level and patient management efficiency of the thoracic surgery intensive care unit are remarkably improved.

The invention discloses an enterprise information visual management system and method based on data sharing, and belongs to the technical field of enterprise information management.The method comprises the steps that by connecting business systems in an enterprise, user behavior data and business data are collected and preprocessed, and an internal data set is constructed; acquiring data from an external data source, and constructing an external data set through semantic analysis, screening and classification; internal and external data are integrated, a dynamic cleaning rule is formulated, multi-source fusion is realized through data association, data are stored in a classified manner according to business requirements, and a data warehouse with a layered architecture is constructed; meanwhile, a personalized data mart is generated based on user roles and permissions, user demands are automatically predicted, and analysis indexes and dimensions are pre-generated; and finally, constructing a visual analysis platform, generating a preliminary recommendation scheme in combination with the pre-generated content and the user operation track, fusing user-defined setting, and outputting a final visual result in real time, thereby realizing efficient management and visual presentation of enterprise information.

The invention belongs to the technical field of bidding and tendering information management, and particularly provides a bidding and tendering information management method and system based on an electronic bidding and tendering transaction platform, and the method mainly comprises the steps: obtaining the original data of a bidding file; performing structured extraction and version calibration on the original data of the bid invitation file to obtain a versioned key clause set; performing change relation chain construction and response feasibility verification on the versioned key clause set to obtain a dynamic association body; obtaining a bidding file; performing rule-driven equivalent matching on the dynamic association body and the bidding file to obtain a bidding response mapping table; and performing bid evaluation rule synchronization processing on the dynamic association body to obtain an adapted bid evaluation rule. The bidding and tendering information processing efficiency and accuracy are effectively improved, full-process transparent management is realized through visual presentation, human intervention risks are reduced, fairness and normalization of bidding and tendering activities are guaranteed, and the scientificity and intelligent level of bidding and tendering management is remarkably improved.

The invention provides a visual detection device and method for building engineering wall quality, and the method comprises the steps: firstly obtaining a multi-angle image set of a to-be-detected wall, which comprises surface images and internal structure scanning images under different illumination conditions, and then carrying out the visual feature extraction of the multi-angle image set, according to the method, a comprehensive visual detection feature set covering surface integrity, internal crack distribution and material uniformity features is obtained, defect area positioning processing is performed on the comprehensive visual detection feature set based on a preset quality evaluation rule, a defect distribution map is generated, and then a visual quality report is generated according to the defect distribution map. And finally, the visual quality report is transmitted to terminal equipment to trigger wall maintenance operation, so that comprehensive and accurate detection and visual presentation of the wall quality are realized, wall maintenance can be effectively guided, and the construction engineering wall quality guarantee level is improved.

The invention discloses an offshore wind power fault monitoring method based on a knowledge graph and digital twinning, and aims to solve the problems that multi-source data acquisition is dispersed, the transmission delay is high, and real-time convergence and integration are difficult to realize in the operation state monitoring of offshore wind power equipment. According to the invention, the following modules are provided: a multi-source data acquisition layer is used for solving the problems of dispersed data acquisition and transmission lag and ensuring the real-time performance; the knowledge graph construction module is used for solving the problems of extraction, fusion and storage of equipment entity relationships; the digital twin modeling module realizes visual presentation and accurate simulation of the state of physical equipment; the fault monitoring reasoning module solves the problems of anomaly detection and root cause positioning; the intelligent early warning decision module determines an early warning level and efficiently matches a solution; the visual interaction module solves the problems of scattered information display and poor linkage, supports third-party docking, realizes accurate early warning and root cause positioning, improves the decision-making efficiency, adapts to severe environments, supports large-scale wind power plant monitoring, and reduces the operation and maintenance cost.

The invention provides a leasing equipment full life cycle monitoring method and system based on the Internet of Things, and belongs to the technical field of equipment operation and maintenance monitoring, and the method comprises the steps: obtaining real-time state data of leasing equipment in an operation process through a multi-source sensor; performing feature extraction on the real-time state data to obtain various feature vectors, and constructing a multi-dimensional feature vector set; inputting the multi-dimensional feature vector set into a random forest model, and judging whether the leasing equipment is in an abnormal state or not in combination with a space-time clustering algorithm; if yes, fault prediction is carried out on the leasing equipment in combination with an abnormal detection result, historical operation data and a baseline model, and a fault probability value of the leasing equipment is obtained; the future position of the leasing equipment is predicted based on the position data, an electronic fence boundary is set for the leasing equipment, if the future position exceeds the electronic fence boundary, an early warning notification of trajectory deviation is generated, and the system finally realizes trajectory and fault visual presentation in a thermodynamic diagram mode, so that the equipment operation and maintenance intelligence and management precision are improved.

The invention discloses a processing method and system for presenting double intelligent agents based on business disassembly and visualization. The processing method comprises the following steps: receiving a natural language request of a power system by a service disassembling agent, carrying out semantic analysis on the natural language request through a small language model, and executing semantic retrieval based on a power system knowledge graph to realize intent recognition and task disassembling of knowledge enhancement. Generating a corresponding task instruction chain by using a directed acyclic graph structure; the task instruction chain is sent to an instruction registration center, the instruction registration center dispatches a visual presentation agent, and an interactive instrument panel and a natural language abstract are generated through a large language model. According to the technical scheme, automatic understanding and efficient decomposition of power system services are achieved, the intelligence and automation level of data processing and visualization is improved, the task scheduling and management capacity of the system is enhanced, manual intervention is effectively reduced, and the operation and maintenance efficiency and the data display accuracy are improved.

A security platform employs a variety techniques and mechanisms to detect security related anomalies and threats in a computer network environment. The security platform is “big data” driven and employs machine learning to perform security analytics. The security platform performs user / entity behavioral analytics (UEBA) to detect the security related anomalies and threats, regardless of whether such anomalies / threats were previously known. The security platform can include both real-time and batch paths / modes for detecting anomalies and threats. By visually presenting analytical results scored with risk ratings and supporting evidence, the security platform enables network security administrators to respond to a detected anomaly or threat, and to take action promptly.

The invention relates to the technical field of defect detection, and discloses an intelligent identification and distribution visualization method and system for weld defects, and the method comprises the steps: collecting a weld ray detection image, carrying out the denoising of the image, obtaining a smooth image, carrying out the multi-scale feature extraction, and obtaining a weld segmentation image through semantic segmentation; a convolutional neural network is adopted to classify different defect types, pixel labeling is carried out, and a defect labeling image is obtained; performing uniform grid division on the welding seam segmentation image, and filtering boundary pixels to obtain an optimized sub-region set; calculating a quantitative proportion of defect pixels and total pixels in the sub-regions, comparing the quantitative proportion with a preset proportion threshold value, then completing classification, and mapping the quantitative proportion to a two-dimensional matrix to obtain a density distribution matrix; the proportion values are aggregated in the length and width directions of the welding seam, and missing data points are filled to obtain a continuous proportion value sequence; and corresponding colors are distributed for the proportion values, and a defect distribution thermodynamic diagram is obtained after rendering. According to the method, high-precision detection and visual presentation of weld defects can be realized.

The invention relates to the technical field of intelligent management of carbon emission of low-carbon engineering, and discloses a typical low-carbon engineering carbon reduction investment intensity measuring and calculating system, which acquires operation data of low-carbon engineering such as offshore photovoltaic engineering through multi-sensor redundancy, ensures credible storage of the data by utilizing a block chain technology, and predicts environment and market factors by adopting a deep learning model. The system power is dynamically distributed based on a multi-objective optimization algorithm, the carbon reduction investment intensity is automatically calculated in combination with the investment cost and the carbon emission reduction amount, and visual presentation and intelligent early warning are achieved through the digital twinborn technology. According to the method, the technical problems that the existing low-carbon engineering carbon reduction benefit evaluation is inaccurate and the investment income is difficult to quantify are solved, and the scientificity and the accuracy of low-carbon engineering investment decision making are improved.

The invention provides a textile culture knowledge visual presentation method and system combined with virtual reality, and the method comprises the steps: firstly obtaining a target textile culture data set containing the textile technology, history and material attribute information, and constructing a three-dimensional textile model set containing a plurality of textile culture element three-dimensional models based on the target textile culture data set; dynamically matching the three-dimensional model with a corresponding textile culture data unit according to a preset rule to generate a virtual reality textile culture scene, then responding to an interaction operation instruction of a user in the scene, extracting interaction behaviors and semantic features, and finally adjusting three-dimensional model display parameters according to the interaction behaviors and the semantic features. And the updated virtual reality textile culture scene is rendered and output in real time, so that vivid and interactive display of textile culture knowledge is realized.

The invention relates to the technical field of digital twinning, in particular to a digital twinning monitoring system for a precision servo press production line, which comprises a physical production line module, an edge calculation module, a cloud digital twinning module and a visual monitoring module, wherein the physical production line module is used for monitoring and collecting production line data in real time; the edge calculation module preprocesses and analyzes the collected original data, judges product defects, equipment faults and employee abnormal states in real time to trigger edge early warning, and outputs a multi-dimensional data set; the cloud digital twinborn module is used for constructing a digital twinborn body, establishing a real-time coupling simulation model fusing electromagnetism, heat, force and sound to simulate the internal physical process of equipment in real time, predicting the performance change and potential fault of the equipment, positioning the fault root cause and predicting the residual life; and the visual monitoring module is used for carrying out multi-dimensional visual presentation and providing decision support. Therefore, the problems of insufficient production line staff monitoring, single physical field monitoring, lack of fault predictability and the like are solved.

The invention discloses a digital animation role dynamic generation method based on a generative model. The method comprises the following steps: inputting a role original image and scene background information, extracting skeleton key points and scene features, analyzing an action sequence, predicting a motion track, calculating an optimal position of a role in a picture, and carrying out dynamic adjustment. And according to the role position, obtaining morphological feature data, evaluating the quality grade, and optimizing the coordination of the role image. And finally, comprehensively scoring by adopting a multi-dimensional quality evaluation system, and determining the visual presentation quality of the role. According to the method, deep fusion of role actions, positions and scenes is realized, the dynamic expressive force and visual coordination of animation pictures are improved, and an efficient solution is provided for generating high-quality animation contents.

The invention discloses an intelligent geophysical exploration geological exploration analysis system, and relates to the field of geological exploration, and the system comprises a collection and preprocessing module which is used for carrying out the adaptive collection of multiple types of geophysical field signals of a target exploration region, and synchronously carrying out the preliminary noise reduction and quality optimization of original signals through signal purification processing; the fusion module is used for receiving the preprocessed multi-type geophysical field signals and carrying out normalization and feature depth correlation fusion on coordinates of data of different dimensions through spatial-temporal feature correlation processing; the method can dynamically adapt to environmental noise optimization signal acquisition, extracts stratum recessive characteristics through multi-dimensional data fusion and intelligent mining, constructs an accurate three-dimensional geologic model, positions stratum attribute deviation and grades through multi-scale analysis, presents exploration results in combination with three-dimensional visualization, and generates target region optimization suggestions.

The invention relates to the technical field of ultrasonic detection, and provides an aero-engine fuel control valve leakage amount ultrasonic detection method, which forms a coherent technical link through leakage ultrasonic signal acquisition, leakage signal separation, leakage feature extraction, leakage area positioning, offset compensation and cross validation of a sensor, and the links are mutually verified and optimized. A leakage signal is separated through a dynamic threshold value, the identification degree of a deep belief network is enhanced through multi-dimensional features, environment interference is compensated and corrected through working condition parameters, positioning deviation caused by single-link error accumulation in a traditional method is effectively restrained, accurate capturing and positioning of a micro leakage signal are achieved, and the method is suitable for large-scale popularization and application. The leakage thermodynamic diagram integrates leakage rate grading, coarse positioning area and micro leakage point information, the analysis and decision-making time of maintenance personnel is greatly shortened through a visual presentation mode, and rapid interpretation of fault positions and severity is achieved.

The invention relates to the technical field of three-dimensional image processing, in particular to an artware three-dimensional dynamic display method and system and a storage medium. The method comprises the following steps: extracting initial handicraft point cloud data from a flexible handicraft sample, and carrying out flexible handicraft microstructure quantification to generate microstructure quantification data; analyzing a macroscopic deformation mode of the drape according to the microstructure quantitative data, updating a real-time deformation geometric grid, and generating artware deformation geometric grid data; performing surface visual feature mapping and visual feature rendering on the artware deformation geometric grid data to generate an artware three-dimensional dynamic picture; and carrying out three-dimensional interactive dynamic display picture generation on the three-dimensional dynamic picture of the artware to obtain an interactive visual presentation frame. Accurate simulation of real wrinkle deformation and microscopic optical characteristics of the flexible handicraft in a three-dimensional space is realized, so that a highly vivid dynamic display effect is provided.

The invention discloses a transcranial alternating current stimulation system and a transcranial alternating current stimulation method based on event-related potential double-component alignment. The system comprises an individualized feature extraction module, a dynamic phase mapping module, a real-time synchronous triggering module and a closed-loop feedback module, wherein the individualized feature extraction module extracts an ERP component latency period and a dominant oscillation frequency based on task state electroencephalogram data; the dynamic phase mapping module establishes phase alignment of an ERP component time window and a tACS waveform to realize a brain oscillation control process; the real-time synchronous triggering module calculates an evoked potential incubation period and a visual presentation incubation period of a corresponding task item, accurately matches a peak value of the evoked potential with a corresponding peak value of a tACS waveform, reads a current phase of the tACS waveform in advance, performs prospective prediction, adjusts the starting time of each stimulation, and realizes millisecond-level stimulation synchronization; the closed-loop feedback module monitors the brain state on line and dynamically corrects alignment parameters to ensure that the stimulation effect is stable; according to the method, accurate phase alignment of tACS and brain endogenous ERP components is realized, neural activities in a specific cognitive process can be effectively enhanced or inhibited, and the accuracy and individualization level of neural regulation and control are improved.

The invention discloses a large-scale people flow evacuation simulation method considering congestion state real-time decision, and belongs to the technical field of crowd emergency evacuation, and the method comprises the steps: S1, obtaining to-be-evacuated crowds, protection places and road network data in a region; s2, constructing a road passing time calculation model; s3, constructing a protection place full-load early warning model; s4, constructing a shortest time flow model considering a congestion state real-time decision; s5, obtaining a crowd evacuation movement process by utilizing crowd simulation, and performing visual presentation; the method is high in simulation efficiency and good in precision, and has good accuracy and practicability for crowd evacuation simulation.

The invention provides a railway engineering information model lightweight management method and system, a storage medium and a computer program product. The method comprises the following steps: receiving uploaded original railway engineering information models from different sources; standardizing the model data format and the model detail level of the original railway engineering information model to obtain a standardized railway engineering information model; reducing the geometric complexity of each component contained in the standardized railway engineering information model by using a geometric simplification mode, and simplifying attribute information contained in the standardized railway engineering information model according to a preset standard to obtain a lightweight railway engineering information model; wherein the geometric simplification mode comprises the step of replacing geometric shapes contained in all the components with regular voxels; and carrying out visual presentation on the lightweight railway engineering information model by utilizing a virtual reality-based mode. According to the invention, lightweight management of the BIM model can be realized.

Provided are systems and methods for multi-garment virtual try-on and editing, example implementations of which can be referred to as M&M VTO. The proposed systems allow users to visualize how various combinations of garments would look on a given person. The input for this method can include multiple garment images, an image of a person, and optionally a text description for the garment layout. The output is a high-resolution visualization of how these garments would look on the person in the desired layout. For instance, a user can input an image of a shirt, an image of a pair of pants, a description such as “rolled sleeves, shirt tucked in”, and an image of a person. The output would then be a visual representation of how the person would look wearing these garments in the specified layout.

The invention discloses a community governance method based on digital twinning, and the method comprises the steps: carrying out the layering and household-splitting modeling of buildings in a community, and building a spatial layout model of roads, greening and Internet of Things equipment, so as to construct a community three-dimensional digital twinning pedestal; real-time data of population track, vehicle passing, elevator running state, dog behavior and high-altitude object throwing events are obtained through Internet of Things equipment and synchronized to community dynamic data in real time; the real-time data is associated with a digital twin base, an interactive three-dimensional visual interface is generated, and personnel flow, vehicle tracks, elevator states and event alarm information are dynamically displayed; and analyzing the collected data based on a machine learning algorithm, and generating a resource configuration optimization strategy, a risk early warning instruction and an emergency response scheme. The method can solve the problem that the existing community public security governance means is mainly based on webpage end disposal and lacks visual presentation and later prevention drill ability.

The invention relates to the technical field of picture synthesis, and discloses a conference multi-source picture synthesis method and device for video access equipment, and the method comprises the steps: carrying out the conference picture quality evaluation and video content short-time dynamic analysis of video streams of multi-party conference participants accessing the video access equipment, and obtaining a conference priority mapping table; making a multi-source conference picture arrangement decision by using the conference scene intelligent multi-modal model to obtain a conference layout description object; performing dynamic frame sampling processing of a predefined conference layout template on the video streams of the multi-party conference participants to obtain a conference sampling video stream set; conference visual presentation integration and conference network adaptive strategy adjustment are carried out, and a multi-source synthetic conference video stream is output, so that accurate capture and priority evaluation of important moments in the conference process are realized, the intelligence of picture switching and the accuracy of opportunity grasping are improved, the definition and fluency of visual key contents are ensured, and the user experience is improved. And the overall resource consumption of the system is reduced.

The invention relates to the technical field of three-dimensional modeling, in particular to an indoor space visual presentation system and method, and the system comprises a contour modeling module, an interference detection module, a path optimization module and a deformation feedback module. According to the method, a geometric structure is constructed through a non-uniform rational B-spline algorithm to realize automatic generation of a topological relation, a two-dimensional contour line is established in combination with a perspective projection converter to eliminate an artificial translation error, line segment intersection detection and hierarchical clustering analysis cooperatively improve interference identification precision, and collision prediction prejudges contour change based on a multi-directional displacement vector. A free deformation grid and a vertex shader are linked to realize surface dynamic updating, a closed-loop process from three-dimensional modeling to visual feedback is formed, the dynamic analysis capability of a spatial relationship is enhanced, automatic contour generation and real-time deformation compensation reduce manual intervention, a path optimization and deformation feedback iteration system is constructed, and the dynamic analysis capability of the spatial relationship is improved. And the visual interference response timeliness and the space adaptation accuracy are improved.

A machine task tutorial system is disclosed that utilizes augmented reality to enable an expert user to record a tutorial for a machine task that can be learned by different trainee users in an adaptive manner. The machine task tutorial system advantageously utilizes an adaptation model that focuses on spatial and bodily visual presence for machine task tutoring. The machine task tutorial system advantageously enables adaptive tutoring in the recorded-tutorial environment based on machine state and user activity recognition. The machine task tutorial system advantageously utilizes AR to provide tutorial recording, adaptive visualization, and state recognition. In this way, the machine task tutorial system supports more effective apprenticeship and training for machine tasks in workshops or factories.

The invention provides a document processing method and device. The method comprises the steps of obtaining a to-be-processed demand document; calling an intelligent agent to perform format conversion on the to-be-processed demand document based on prompt information associated with the intelligent agent to obtain a structured tagged document in a markup language format returned by the intelligent agent; the prompt information is obtained by filling a prompt template of an intelligent agent based on a sample demand template obtained in response to the selection operation, and the prompt information is used for guiding the intelligent agent to perform structured recombination and formatted output on the content of the demand document to be processed according to structured fields and levels defined in the sample demand template; on the basis of the structured marking document, the configured online structured template is filled, and the online structured demand document supporting visual presentation and / or interactive editing is generated, so that the document processing efficiency and accuracy are improved, errors and omissions possibly occurring in manual processing are avoided, and the user experience and the working efficiency are improved.