230results about How to "Quick understanding" patented technology

The embodiment of the invention discloses a bridge bolt monitoring image recognition method and system based on deep learning, and belongs to the technical field of bridge image processing. The method comprises the following steps: acquiring a multi-angle monitoring image set of a bridge bolt part through an image acquisition device, and preprocessing the monitoring image set to generate a standardized target image sequence; positioning a bolt monitoring area for each image frame in the target image sequence based on a pre-trained positioning model, and generating an area coordinate set containing bolt position information; inputting the region coordinate set into a state recognition model, extracting structural state features of each bolt monitoring region, and generating a looseness degree prediction result of the bolt part according to the structural state features; according to a matching result of the looseness degree prediction result and a preset safety threshold range, a bolt state abnormity alarm signal is output; and associating the bolt state abnormity alarm signal to the corresponding monitoring image frame, and generating a monitoring report containing a visual mark.

The invention provides a brain parenchyma MRI image-based infarction change prediction method and system, and relates to the technical field of image recognition, and the method comprises the steps: obtaining a brain parenchyma MRI image, constructing a multi-modal image set, carrying out the screening according to a screening standard, carrying out the artifact recognition, calculating a quality score, carrying out the preprocessing, obtaining standard image data, carrying out the feature extraction, and carrying out the prediction of the infarction change of the brain parenchyma MRI image. Obtaining a brain region segmentation mask; performing feature extraction to obtain multi-modal feature data, constructing a topological relation among different brain regions, extracting high-order semantic features, obtaining brain region feature data, and performing selection to obtain high-quality feature data; constructing a time sequence characteristic matrix, distributing weights, generating residual output, performing prediction through a full-connection neural network, generating an infarction change prediction result, generating a prediction prognosis result, and generating a comprehensive prediction report.

The invention provides an electrocardiogram data anomaly recognition method, device and equipment based on deep learning and a storage medium. An original electrocardiogram signal of a patient is collected, and a target electrocardiogram signal is obtained through multi-stage preprocessing. And identifying an abnormal signal in the target electrocardiogram signal by using a deep fusion learning model, and generating a preliminary identification result. And then, the preliminary recognition result is combined with a pre-trained machine learning model, mixed model processing is performed through a stack generalization fusion method, a Bayesian network is constructed based on the detailed information of the patient, a reasoning result with context sensing is obtained, and a target recognition result is finally generated. And generating an abnormal report according to the target identification result, and storing and displaying the abnormal report to the user in a classified manner according to a predefined standard. According to the method, high precision and personalized diagnosis of anomaly detection are ensured, and the reliability and efficiency of electrocardiogram analysis are improved.

The embodiment of the invention discloses a chip register description document generation method and device, a storage medium and terminal equipment, and relates to the field of document processing. The method comprises the following steps: analyzing a register attribute table file of a chip, and determining each functional module included in the chip and a register included in each functional module according to an analysis result; querying an associated register description template document according to the model of the chip; extracting field values corresponding to fields in the register list display area and the register description display area from the register attribute table file, and filling the read field values into a register description template document to generate a register description document of the chip, the problems that in the prior art, compiling of the chip register description document is low in efficiency, prone to errors and poor in timeliness are effectively solved, and a more efficient, accurate and reliable method is provided for compiling and managing the chip document.

The invention provides a ground surface settlement monitoring method and system fusing Beidou and InSAR data. The method comprises the following steps: receiving positioning data from a Beidou satellite system and earth surface deformation data acquired by a synthetic aperture radar interference measurement system; based on the positioning data and the earth surface deformation data, correcting the earth surface deformation data according to the environmental factors through a space-time fusion model to obtain corrected earth surface deformation data; by means of the corrected surface deformation data, a multi-stage analysis technology is adopted, the development trend of surface subsidence is determined, a surface subsidence distribution diagram is generated, and the surface subsidence distribution diagram is used for displaying spatial distribution characteristics of surface subsidence; and according to the ground surface settlement distribution diagram, the future ground surface settlement condition is monitored by using the space-time fusion model, and a ground surface settlement monitoring report can provide a scientific basis for early warning and prevention of geological disasters. The ground surface settlement monitoring efficiency and monitoring effect are improved.

The invention discloses pre-hospital emergency medical aid emergency help integrated equipment and system. The method comprises the following steps: S1, acquiring key vital sign data of a patient by using medical equipment; s2, calling basic information and medical history of the patient through equipment; s3, transmitting the collected data to a server of a remote data processing center in real time; s4, performing comprehensive analysis on the received vital sign data and the medical history information of the patient by applying a pre-trained deep learning model on the server, and generating a prediction report; s5, displaying a prediction result on a portable device or a remote monitoring station in real time by using a data visualization technology; s6, based on a visual prediction result and medical history analysis, guiding first-aid personnel to take targeted emergency medical measures; and S7, continuously monitoring the vital sign response of the patient and any health change related to the medical history, and updating the treatment strategy according to the further analysis of the deep learning model.

The invention discloses an intelligent medical pre-inquiry method and system based on a multi-modal large model and a medium, and the method comprises the steps: obtaining user input data to recognize a target intention, and when a knowledge question and answer intention is recognized, obtaining a knowledge question and answer module; based on the medical knowledge graph, combining with knowledge keywords in the user input data and utilizing a multi-modal large model to obtain medical answers; when the pre-inquiry intention is recognized, inquiry keywords in the user input data are extracted for slot filling to obtain slot information, and a slot filling strategy is dynamically adjusted based on the slot information and user feedback data; and performing visual display on the medical answers and the health management suggestions based on the user interaction interface, and obtaining user interaction data for human-computer interaction. According to the invention, a natural language processing and multi-modal fusion mode is adopted, so that the information input process of a patient is more convenient; and meanwhile, by introducing dynamic medical history information acquisition and interaction, real-time interaction with the patient is realized, and the user experience of pre-inquiry is improved.

The invention discloses a brake spring piece flatness detection system and method, and relates to the technical field of automobile part processing. The brake spring piece flatness detection system comprises a data acquisition module, a data analysis module, a data screening module, a dynamic monitoring module and a comprehensive judgment module, wherein the data acquisition module is used for acquiring static detection data of N groups of spring pieces randomly extracted from the same batch; the static detection data comprises top view shooting picture data and side view shooting picture data of N groups of spring pieces, which are acquired at equal intervals by utilizing an optical detection instrument, and size data of the spring pieces, which are acquired by utilizing a laser radar, and the technical key points are as follows: through analysis and processing of the static detection data and the dynamic detection data, the overall quality of the spring pieces is shown; related workers can conveniently and quickly know whether the spring pieces meet the requirements of automobile braking or not, high-quality products can be quickly screened out from numerous spring pieces, use is convenient, secondary detection is not needed in the follow-up process, and good application prospects are achieved.

The invention provides a semantic similarity analysis method for science and technology project management, and belongs to the technical field of information, the semantic similarity analysis method for science and technology project management comprises the following steps: preprocessing collected project documents, including text cleaning, word segmentation and stop word removal; extracting vocabulary features in the document, and converting the vocabulary features into numerical vector representation; calculating the semantic similarity between the documents or terms; and applying a similarity analysis result to document management and information retrieval: performing automatic preprocessing on the document, including text cleaning, word segmentation, stop word removal and standardization processing, so that a system can quickly prepare document data, prepare for subsequent analysis, automatically extract vocabulary features in the document by using an advanced word embedding model (such as Word2Vec, GloVe or BERT), and perform data processing on the document. And the information is converted into a numerical vector for representation, so that the requirement of manual intervention is greatly reduced.

The invention discloses a data processing method and device based on a visual database and electronic equipment, and relates to the field of data processing. The method comprises the following steps: acquiring a data processing request of a user; analyzing the data processing request to obtain a corresponding key field and a logic conjunction; according to the key field, performing semantic matching in a preset data model library to obtain a corresponding target data table and a target field; synthesizing the logic conjunction, the target data table and the target field to generate a corresponding database processing statement; executing the database processing statement, and obtaining a result data set generated after the database processing statement is executed; and transmitting the result data set to a visual database terminal, and displaying the result data set on the visual database terminal according to a preset visual template. By implementing the technical scheme provided by the invention, the data query efficiency is improved.

The invention provides a multimedia resource playing method and device, equipment and a storage medium, and belongs to the technical field of multimedia. The method comprises the steps that in the process of playing a multimedia resource, an interaction object is displayed, the multimedia resource is used for introducing a target object, and the multimedia resource is associated with a first virtual resource related to the target object; in response to an interaction operation on the interaction object, playing the multimedia resources at multiple speeds; in response to the multimedia resource playing to the preset progress, receiving success information is displayed, and the receiving success information is used for indicating that the first virtual resource is successfully received. According to the technical scheme, a scheme for playing the multimedia resources at multiple speeds through the interactive operation can be provided, and the information acquisition efficiency and the man-machine interaction efficiency are improved.

The invention discloses an intelligent security monitoring and early warning method and system for an industrial control network, relates to the technical field of network security monitoring, and can collect multi-dimensional data such as network traffic, user behaviors and equipment states in real time through a data acquisition module and a system to ensure the timeliness and comprehensiveness of monitoring. Therefore, potential security threats can be quickly identified, and the overall security protection capability is improved. And the data preprocessing module cleans and standardizes the collected data, so that the data quality and consistency are improved, a reliable basis is provided for subsequent risk assessment, and misjudgment caused by data inconsistency is reduced. And the risk assessment module calculates a comprehensive risk index through a multi-dimensional assessment formula, different types of security threats can be identified more accurately, and a scientific basis is provided for a subsequent early warning mechanism. The multi-level early warning mechanism module divides the risk into a low level, a middle level and a high level according to the comprehensive risk index, and a targeted response strategy can be realized.

The invention relates to the technical field of breach image processing, in particular to a breach rapid situation awareness method and system based on multi-source data. The method comprises the following steps: acquiring dam monitoring station data; performing hydrological sensor network setting on the dam monitoring station data to obtain dam hydrological sensor network data; performing ultrasonic water level change trend analysis on the dam hydrological sensor network data to generate an ultrasonic water level change trend chart; performing breach node sensing on the dam hydrological sensor network data according to the ultrasonic water level change trend chart to generate breach node data and breach prediction node data; and according to the breach node data, macroscopic disaster risk analysis is carried out on the breach area, and a breach area macroscopic disaster risk schematic diagram is generated. According to the invention, through real-time data integration, comprehensive risk assessment, unmanned aerial vehicle monitoring, dynamic prediction model and multi-party cooperative response, the accuracy and response speed of breach rapid situation awareness are improved.

The invention discloses a multi-modal large model small sample classification method based on knowledge enhancement, and relates to the field of artificial intelligence and computer vision, and the method comprises the steps: collecting a multi-scene image data set, and constructing base class and new class data into a small sample instruction fine tuning set and a test set which accord with a meta-learning normal form; enhancing the picture and text labels of the fine tuning set, and inputting the multi-modal large model for fine tuning; in the reasoning stage, historical dialogues and instructions in a test set are randomly selected and input into the fine-tuned model together to obtain an initial classification result; then, generating a plurality of attribute descriptions for each image, calculating the similarity of the descriptions among the images, and sorting the descriptions to screen reliable candidate answers; finally, the reliability of the initial answer is judged, and if the initial answer is not reliable, a new candidate answer construction instruction is used for reasoning again. According to the method, the small sample classification capability of the multi-modal large model is improved through a knowledge enhancement method based on two stages of fine adjustment and reasoning, and the method is suitable for general and fine-grained classification tasks.

The invention provides a big language model-based intelligent analysis system for a newly created enterprise, and the system comprises a data collection module which is used for collecting data of the newly created enterprise; the data preprocessing module is used for preprocessing the data of the initially created enterprise; the vector database and knowledge graph construction module is used for constructing a vector database and a knowledge graph based on the preprocessed initially created enterprise data; the context information construction module is used for carrying out deep semantic analysis on related information, input by a user, of the to-be-analyzed enterprise, and fusing a semantic analysis result with data of the vector database and the knowledge graph to obtain context information; and the intelligent analysis module is used for carrying out intelligent analysis on the context information based on the initially created enterprise research analysis auxiliary large model, obtaining development state data of the to-be-analyzed enterprise, and completing initially created enterprise intelligent analysis based on the large language model. And comprehensive and efficient retrieval and processing of related data of the initially created enterprise are realized.

The invention discloses a PICC (Peripherally Inserted Central Catheter) positioning examination method based on an X-ray chest radiograph and a related device. The method comprises the following steps: acquiring an X-ray chest radiograph image of a target patient; establishing an X-ray chest radiography PICC positioning model to identify an anatomical structure and a PICC catheter path in the X-ray chest radiography image; the X-ray chest radiography PICC positioning model comprises an anatomical structure identification unit, a catheter path identification unit and a position evaluation unit; the anatomical structure identification unit is used for identifying an anatomical structure in the X-ray chest radiography image; the catheter path identification unit is used for identifying a PICC catheter path in the X-ray chest radiography image, and the PICC catheter path comprises a starting point, a walking path and a tail end position of a catheter; the position evaluation unit is used for evaluating the position of the tail end of the catheter according to the anatomical structure and the PICC path and generating a position evaluation result; and examining the positioning of the PICC according to the position information text of the tip of the PICC and the position evaluation result. The accuracy and efficiency of PICC positioning examination are improved through the X-ray chest radiography PICC positioning model.

The invention relates to the technical field of data processing, in particular to an intelligent recommendation system fusing big data and AI, and the system comprises a scheme obtaining module which obtains a plurality of target marketing schemes; the scheme analysis module analyzes a plurality of target marketing schemes to determine a plurality of marketing features; the data acquisition module collects a plurality of historical behavior data of a user; the data analysis module analyzes a plurality of historical behavior data to determine user characteristics; the association determination module analyzes association between the user features and the plurality of marketing features based on the initial association AI model, and determines prediction priorities of the plurality of target marketing schemes based on an association analysis result; a recommendation module constructs a user recommendation page based on the predicted priority, and determines target priorities of a plurality of target marketing schemes based on the real-time behavior data of the user; and the feedback module compares a comparison result of the prediction priority and the target priority to adjust the initial association AI model to obtain a target association AI model. According to the invention, the accuracy of personalized marketing scheme recommendation of the user is improved.

The invention relates to the technical field of software security, in particular to a decentralized financial platform loan intelligent contract vulnerability detection method and system based on a graph neural network, and the method comprises the steps: collecting intelligent contract source code data, and carrying out the vulnerability marking of the intelligent contract source code data according to whether there is a vulnerability in the data; compiling intelligent contract source code data into an abstract syntax tree, and constructing a contract code heterogeneous graph; constructing a graph neural network model, and performing vulnerability prediction training on the graph neural network model by using the contract code heterogeneous graph to obtain an intelligent contract vulnerability detection model, the graph neural network model captures structural features of a contract code heterogeneous graph layer by layer by using a hierarchical attention enhancement mechanism and predicts and identifies vulnerabilities in contract codes based on the structural features; and converting the to-be-detected smart contract source code into a target contract code heterogeneous graph to perform vulnerability prediction on the target contract code heterogeneous graph. According to the method, the semantics and data flow characteristics of the contract can be accurately captured, and efficient and accurate detection of the intelligent contract vulnerability is realized.

The invention discloses an intelligent beam field construction management system based on BIM and GIS, and relates to the technical field of beam field construction management. Main parameters of a beam field construction environment can be fully covered by deploying a temperature and humidity sensor, an air quality sensor, a noise sensor, a wind speed and direction sensor and a rainfall sensor; spatial data association is performed on the BIM model by using a spatial analysis tool in a GIS platform, geographic information and construction in the BIM model are subjected to geographic space matching, and the accuracy of an association result is ensured through verification, so that data integration and sharing are facilitated, the use efficiency of the data is improved, and the method is suitable for popularization and application. A construction supervisor can monitor the construction progress according to the tracking data recorded in real time, a construction plan is adjusted in time, and smooth construction is ensured.

The invention relates to the technical field of electronic component data processing, in particular to a database construction method and system based on electronic components. The method comprises the following steps: carrying out component information acquisition through an electronic component transaction platform to obtain an original component data set; performing component relation mapping construction according to the original component data set to obtain a component association graph; performing multi-dimensional attribute extraction on the component association map to obtain component attribute vectors; performing component similarity calculation and clustering analysis according to the component attribute vector to obtain a component cluster; and extracting pin information according to the component cluster to obtain a cluster pin data set. According to the method, multi-dimensional condition screening, sorting and result explanation are realized, an accurate, reliable and easily understood component replacement recommendation scheme is provided for a user, the user is helped to quickly find a proper component, and the electronic design efficiency is improved.

The invention discloses a multi-dimensional code intelligent analysis method and system based on a visual information pair processing result, and aims to simulate a rapid understanding and recognition process of human on a complex scene. According to the method, multi-dimensional scene grid information which is formed by processing results based on visual spatio-temporal information and has depth-of-field information is coded, in the coding process, feature extraction, multi-dimensional code generation and redundancy check multi-dimensional code coding technologies are adopted to convert complex scene information into an efficient and compressed coding form, and the codes are stored in a database; after a scene is quickly coded, the scene is matched with stored multi-dimensional code information, so that quick understanding and accurate recognition of the scene are realized. Through the efficient multi-dimensional code encoding and processing method, a new technical framework is provided for intelligent and rapid scene processing, the scene recognition and understanding ability of a complex environment is improved, and powerful technical support is provided for humanoid robots, pilotless automobiles, intelligent glasses and inspection equipment.

The invention discloses an intelligent arrhythmia classification device based on deep learning. The intelligent arrhythmia classification device comprises a data set construction module, a data preprocessing module, an intelligent arrhythmia classification network construction training module and an analysis module, the data set construction module is used for constructing a heart rhythm sample data set, the data preprocessing module is used for expanding the data set by applying a wavelet denoising method and randomly sampling the heart beat type data set with more data distribution by utilizing an undersampling principle, and the arrhythmia intelligent classification network construction training module is used for constructing an arrhythmia intelligent classification network based on a DenseNet-201 network. And carrying out model training by adopting an Adam optimizer and a learning rate attenuation strategy, and classifying the arrhythmia data set. And the analysis module explains a model classification result by utilizing a plurality of methods such as HiResCAM, LIME and SHAP. According to the method, the electrocardiogram can be rapidly analyzed, and the basis for model type judgment can be visually displayed.

The invention provides a mathematical knowledge graph construction method based on big data, and the method comprises the following steps: a plurality of data sources obtain data of a mathematical field, and the data is preprocessed through a natural language processing technology; extracting mathematical concepts, theorems, formulas and relationships among the mathematical concepts, the theorems and the formulas from the preprocessed data by using a deep learning model to form mathematical entities and association relationships thereof; constructing a mathematical knowledge graph by adopting a graph structure according to the extracted mathematical concepts and relationships; reasoning the constructed mathematical knowledge graph through a graph neural network, automatically deducing a new knowledge relationship based on the mathematical knowledge graph, and dynamically updating the mathematical knowledge graph based on knowledge extracted from new mathematical literatures and data. According to the method, the mathematical knowledge graph with self-learning and updating capabilities is constructed by collecting and processing large-scale data in combination with a graph structure and an inference technology, so that the efficiency of mathematical knowledge management can be greatly improved.

The invention discloses a unified multi-version kernel service network traffic acquisition method and system based on a high-performance non-intrusive technology, and belongs to the technical field of computers. The method comprises the following steps: collecting traffic according to a kernel type of an operating system; and analyzing the collected flow data. Through the scheme of the invention, efficient collection of network traffic in various kernel versions and operation environments can be realized, and technical obstacles caused by kernel version differences do not need to be worried about. No matter a high-performance server, a device with a low-version Linux kernel or a container or a cloud environment with limited authority, seamless flow capture and analysis can be realized by using the system provided by the invention. Meanwhile, the protocol analysis and flow topology function helps the user to quickly understand the network condition and output a unified flow index, thereby greatly improving the efficiency of network operation, maintenance and analysis.

The invention provides a presentation document processing method and device, electronic equipment and a storage medium. The presentation document processing method comprises the steps that a presentation document to be processed is determined, and the presentation document comprises a plurality of pages; determining a starting page of each minimum chapter unit of the demonstration document and summary content of the starting page; inputting the presentation document or each start page into a pre-trained first multi-modal model to determine a chapter structure of the presentation document, the chapter structure comprising a chapter title and a corresponding page; processing the chapter structure according to the summary content of the starting page; according to the method, the chapter structure of the demonstration document can be generated, a user can clearly check the hierarchical relation of the whole demonstration document, and due to the fact that the first multi-mode model is adopted, front layout visual input is not needed, and dependence on a system is less.

The invention relates to the field of network equipment analysis, and discloses a situation awareness analysis method based on a network event, which comprises the following analysis steps: a data acquisition module acquires data in network equipment in real time and uploads the acquired data to an analysis module for analysis, and the data comprises network data, equipment working state data and log information; the threat analysis module analyzes the data based on a deep learning algorithm, discovers potential security threats in the network equipment, processes the security threats in time, and obtains a threat coefficient through calculation. The invention further discloses a situation awareness analysis system based on the network events. According to the method, the security situation report is generated according to the scoring result, a visual security situation overview is provided for managers, the report content is detailed and accurate, the managers can quickly know the network security situation and make corresponding decisions, and network security situation awareness is more comprehensive, accurate and efficient.

The invention provides a mud-phase shale component quantitative analysis and calculation method, which relates to the technical field of geological mineral exploration and mainly comprises the steps of sample collection and pretreatment, X-ray diffraction pattern acquisition, pattern analysis and mineral component determination, quantitative calculation based on an innovative model, result correction and evaluation and the like. Through an innovative quantitative analysis model and a strict sample processing flow, the content of various mineral components in the mud-phase shale can be more accurately determined, analysis errors are reduced, more reliable data support is provided for geological research and resource exploration, and compared with a traditional method, the method has the advantages that operation steps are simplified, analysis efficiency is improved, and the method is suitable for popularization and application. According to the method, the quantitative analysis of the mud-phase shale components can be completed in a shorter time, the progress of research and exploration is accelerated, the dependence on complex and expensive chemical analysis equipment is reduced, the experiment cost and the human input are reduced, and meanwhile the utilization efficiency of resources is improved.

The invention discloses an automatic salary data generation method and system for the express industry, and relates to the field of salary data processing, and the method comprises the steps: creating a salary model, naming the salary model, and selecting an applicable person; uploading the historical salary list file of the selected applicable personnel to the system, and obtaining related salary data; analyzing the salary document of the historical months, and obtaining element items of the franchise company; establishing a mapping relation between the franchise company element items and the standard element items through an intelligent matching algorithm; and presenting the generated mapping relation to the financial staff of the franchise company, and adjusting and confirming the matching rule by the financial staff of the franchise company. According to the method, the advanced natural language processing technology is utilized, intelligent analysis of various salary related terms and descriptions is supported, the accuracy and consistency of salary calculation are ensured, automatic salary generation is achieved, a large amount of manpower and time are saved, and better use prospects are brought.

The invention discloses a traditional Chinese medicine analysis and identification system, method, equipment and medium based on a large model, and the system comprises a data collection module which is used for collecting multi-dimensional data of traditional Chinese medicines, a data preprocessing module which is used for carrying out the cleaning, standardization processing and feature extraction of the collected data, and a data analysis module. The data processing module is used for analyzing and processing received data by utilizing a pre-trained deep large model, the result output module is used for outputting an analysis result to a user in a visual manner, and the analysis result output module comprises a visual chart, a detailed report form and an intelligent feedback module according to the feedback of the user on the analysis result and the actual application condition. Through multi-dimensional data acquisition, advanced preprocessing, deep large model analysis and the like, the practicability is improved by modules of accurate identification, intelligent feedback, collaborative analysis and the like of the traditional Chinese medicine, data updating and the like ensure that the system advances with the times, powerful technical support is provided for industrial development of the traditional Chinese medicine, and the quality and safety of the traditional Chinese medicine are guaranteed.

The invention provides a software development system and method based on AR-HUD, electronic equipment and a storage medium. The software development system comprises an external information data transmission module, an application program module and an HUD hardware module. Wherein the external information data transmission module is used for sending related information data of a target vehicle to the application program module; the application program module is used for performing logic function processing on the related information data and acquiring processed result data; and the HUD hardware module is used for carrying out U I and AR information display on the result data. According to the method and the device, the AR-HUD development complexity can be reduced, and the development efficiency is improved.