309results about How to "Improve objectivity" patented technology

The invention relates to the technical field of coal mill powder pipes, in particular to a powder leakage defect automatic identification method based on digital twinning and AI video analysis, and the method comprises the steps: obtaining operation parameters and environmental parameters of a coal mill powder pipe, calculating a powder leakage risk characterization coefficient, and judging whether there is a potential risk of powder leakage; image data of the surface and the surrounding area of the powder pipe in the initial starting period are collected through an AI video analysis module, powder leakage characteristic parameters are extracted, a characteristic change curve segment is drawn, similarity comparison is conducted on the characteristic change curve segment and the reference characteristic curve segment, and whether a suspected powder leakage area exists or not is judged; actual operation parameters and model prediction parameters of the powder pipe in a stable operation period are obtained based on a digital twin model, the fluctuation degree of parameter deviation is calculated, and whether the powder leakage defect exists or not is comprehensively judged by combining a suspected powder leakage area judgment result; the early-stage accurate identification of the powder leakage defect is realized, the detection efficiency and precision are improved, and the operation and maintenance cost and the safety risk are reduced.

The invention discloses a hydraulic structure risk assessment method based on a multilevel dynamic fuzzy Bayesian network, and relates to the technical field of hydraulic engineering safety monitoring, and the method comprises the following steps: recognizing risk factors of a hydraulic structure, and building a hierarchical hydraulic structure risk assessment system; a Bayesian network risk probability model is constructed based on a risk assessment system, nodes in the model correspond to indexes of each layer of the assessment system, and edges among the nodes are connected according to a causal relationship among the indexes. According to the invention, accurate and dynamic management and control of hydraulic structure risks are realized. In the aspects of data processing and risk judgment, multi-source monitoring data such as displacement, seepage and water level are classified and integrated according to an index layer, a criterion layer and a target layer through hierarchical evaluation system design, the isolation problem of traditional single data monitoring is avoided, the data collaboration value is fully mined through logic association among the layers, and the risk judgment accuracy is improved. And the risk assessment does not depend on one-sided information any more.

The invention discloses a sedimentary facies model construction method and device, equipment and a storage medium. The method comprises the following steps: acquiring regional geological parameters of a target construction region; and determining structure interpretation data according to the regional geological parameters, and constructing a three-dimensional structure model according to the structure interpretation data. And analyzing distribution information of each lithofacies in the three-dimensional structure model according to regional logging data, and constructing a lithofacies framework model. A target sedimentary facies model corresponding to the target construction area is constructed according to the three-dimensional sedimentary point cloud and the lithofacies framework model based on a multi-point geostatistics algorithm, and the three-dimensional sedimentary point cloud is obtained by performing actual sedimentary simulation on the target sedimentary construction model obtained through pre-training based on the area geological parameters of the target construction area. According to the technical scheme, the three-dimensional sedimentary point cloud of the research area can be accurately extracted, high geological objectivity and physical authenticity are achieved, and therefore the objectivity and geological reliability of the sedimentary facies model are remarkably improved.

The invention provides a dysphagia screening system based on computer vision, and relates to the technical field of image recognition, and the system comprises an image collection module which collects image data of a swallowing event to obtain a time sequence image sequence; the motion field establishing module is used for extracting a motion point track sequence according to the time sequence image sequence and establishing a global motion transformation field; the motion separation module is used for carrying out registration correction on the global motion transformation field and carrying out motion separation on the stabilized image sequence to obtain local deformation components; the region segmentation module is used for carrying out key region segmentation on the local deformation components to obtain swallowing function parameters; and the risk identification module is used for identifying the obstacle risk of the swallowing function parameters and generating a swallowing obstacle screening report. According to the method and the device, the technical problem of relatively poor screening accuracy of the dysphagia based on the computer vision in the prior art can be solved, and the technical effect of improving the screening accuracy of the dysphagia based on the computer vision is achieved.

The invention discloses a feature analysis and prediction method for drawing a depression patient based on a convolutional neural network, and belongs to the field of artificial intelligence and mental health. The method comprises the following steps: acquiring drawing image data of a depression patient and a healthy control group, and constructing a standardized data set; preprocessing such as denoising, size normalization and edge enhancement is carried out on the image; constructing a convolutional neural network model comprising four convolutional layers, two pooling layers and a feature fusion layer, and automatically extracting key features such as line definition, spatial layout and detail richness by adopting a variable receptive field mechanism and an attention module; correlation analysis is carried out in combination with scores of a clinical evaluation scale, and the model is optimized through transfer learning and a focus loss function; and generating a risk assessment report. According to the method, objectivity and accuracy of depression screening are remarkably improved, subjective evaluation deviation is reduced, visual decision support is provided for clinicians, and early recognition and intervention of depression are achieved.

The invention relates to the technical field of data processing, in particular to an industry chain subdivision industry state judgment method and device based on dynamic weighted scoring. The method comprises the following steps: firstly, obtaining enterprise data and subdivided industry association strength, an industry reference value and a dimension dispersion coefficient in an industry chain knowledge base; setting a core dimension of an industry corresponding to the data, calculating an objective weight of each dimension based on an entropy weight method, and performing fine adjustment on the weights within a dynamic adjustment range according to manual optimization requirements; verifying the validity of the adjusted data through historical data; and carrying out multi-dimensional numerical calculation processing on the data based on an intelligent scoring model, processing the processed data through a threshold value and a weighted value, and judging that the state of the subdivided industry is normal, and needs a strong chain or a supplementary chain and a delay chain. And precise judgment of subdivided industrial states is realized. According to the method, objectivity and adaptability of industry chain analysis are effectively improved, and precise judgment of subdivided industry states is realized.

The invention relates to the technical field of biological detection, and discloses a caenorhabditis elegans reproductive toxicity intelligent evaluation system and an application method.The caenorhabditis elegans reproductive toxicity intelligent evaluation system comprises a standardized exposure and imaging module used for executing a high-flux pollutant exposure experiment under a controlled environment condition and synchronously collecting nematode behavior and gonad image data; and the multi-modal data acquisition unit is connected to the standardized exposure and imaging module and is used for extracting and preprocessing behavioral parameters and reproductive toxicity indexes from the acquired images. According to the method, 12 behavior parameters and 8 core reproductive indexes are automatically extracted by constructing a multi-modal data acquisition unit and utilizing an improved U-Net model and a specific algorithm, so that full-process automation from image acquisition to key index quantification is realized. The problems of low efficiency, large subjective deviation and poor repeatability caused by dependence on manual interpretation in the prior art are solved, and the objectivity of the evaluation result and the high-throughput screening efficiency are remarkably improved.

The present application belongs to the technical field of material corrosion data processing and industrial equipment state monitoring, and provides a kind of multi-source feature extraction and structured expression method of air conditioner heat exchanger corrosion data, specifically comprising the following steps: obtaining multi-source corrosion original data;Data preprocessing;Corrosion morphology feature extraction;Electrochemical feature extraction;Environmental influence feature extraction;Feature normalization processing;Structured feature vector construction;Form a structured feature vector with fixed dimension, unified expression. Each component in the feature vector corresponds to a corrosion-related parameter with clear physical meaning, completely describing the corrosion state, corrosion kinetics characteristics and service environment conditions of the heat exchanger under specific space-time conditions. Advantage: significantly improve the usability of data, provide an ideal data interface for multi-modal data fusion analysis and large model technology application, significantly improve the objectivity and reliability of the analysis results, have strong engineering practical value.

The application relates to the technical field of intelligent control, and discloses a recipe sorting implementation method and device based on a recipe matching result, and a storage medium, which comprises the following steps: after a plurality of matched candidate cooking recipes are screened out based on a to-be-cooked material, for each candidate cooking recipe, a basic matching degree between the candidate cooking recipe and the to-be-cooked material is calculated according to a target parameter corresponding to the candidate cooking recipe, wherein the target parameter comprises recipe coverage and material utilization; the basic matching degree corresponding to the candidate cooking recipe is corrected based on an auxiliary factor corresponding to the candidate cooking recipe to obtain a comprehensive matching degree between the candidate cooking recipe and the to-be-cooked material; and all the candidate cooking recipes are sorted according to the comprehensive matching degree to obtain a candidate recipe sorting result. It can be seen that the application can improve the sorting reliability of cooking recipes, and further improve the matching degree between the recommended cooking recipe and the actual demand of a cooking user and the efficiency of the cooking user in selecting a cooking recipe.

This invention belongs to the technical field of sleep quality analysis, specifically relating to a sleep quality analysis system and method based on sensors in a medical bed, to address the technical problem of existing methods relying too heavily on duration statistics while neglecting the continuity and circadian rhythm of sleep. The analysis method includes: S1, acquiring vital sign signal data collected by sensors in the medical bed within a sleep cycle and dividing it into multiple continuous time segments; S2, extracting physiological indicators such as respiratory rate, heart rate, and body movement amplitude within each time segment, and calculating the variability depth of the corresponding time segment; S3, generating a variability depth baseline; calculating non-steady-state disturbance factors based on the frequency and duration of micro-awakening disturbance segments; and S4, generating a comprehensive sleep quality score. The analysis method of this invention improves the comprehensiveness and objectivity of the assessment results, more realistically reflecting sleep health status.

The invention relates to the technical field of intelligent education, in particular to an intelligent practical operation assessment system and method based on multi-modal perception, and the system comprises a question setting and rule configuration module, a local assessment terminal, a hardware connection monitoring module and a remote management service terminal. The question setting and rule configuration module is used for generating a structured test question rule file, the hardware connection monitoring module is used for collecting conduction relation data, and the local assessment terminal comprises a man-machine interaction layer, a sensing and monitoring layer and an application logic and control layer; the remote management service terminal is used for data storage and instruction issuing. The system has the following advantages and effects: through the cooperation of the question setting and rule configuration module, the local assessment terminal, the hardware connection monitoring module and the remote management service terminal, the operation behavior and the tool state are identified; multi-mode perception, automatic monitoring and accurate scoring of electrician practical training type practical operation assessment are realized, and the objectivity, efficiency and traceability of assessment are improved.

The invention relates to a nursing teaching support system and method based on an infant language vocabulary library, and relates to the technical field of data processing, and the system comprises an intelligent high-fidelity audio collection module which is used for collecting an original audio signal of an infant in real time in a nursing teaching or simulation training environment, carrying out background noise filtering processing on the original audio signal to obtain a pure biological acoustic signal; the pre-crying sound production micro-feature extraction module is used for forming a multi-dimensional acoustic feature vector; the dynamic infant language standardized vocabulary library module is used for obtaining an acoustic semantic resonance index and a demand type and an emergency degree corresponding to each type of physiological demands; the teaching aid decision-making and feedback module is used for calculating the perception deviation of the judgment result and generating graded teaching prompt information; and the multi-dimensional visual teaching interaction module is used for generating a quantitative evaluation report of the pre-judgment ability of the student for the early-stage demands of the baby. The system can improve the effect of infant nursing teaching support.

The application discloses a data processing method and device, a storage medium and an electronic device. It relates to the technical field of medical treatment. The method comprises the following steps: a tibia three-dimensional model is constructed, and a plurality of target steel nail three-dimensional models are obtained; a plurality of second medical images are obtained, and a plurality of target steel nail first two-dimensional pixel point sets and a tibia second two-dimensional pixel point set are obtained according to the plurality of second medical images; target space conversion parameters of the plurality of target steel nails in the tibia coordinates are obtained by calculation according to the target steel nail first two-dimensional pixel point sets, the tibia second two-dimensional pixel point set, the tibia three-dimensional model and the steel nail three-dimensional models; a guide plate model is obtained according to the target space conversion parameters, and a target space posture of a tibia osteotomy plane is obtained according to the guide plate model. Through the application, the technical problem that the space posture of the tibia osteotomy plane is relatively low in accuracy because the space posture of the tibia osteotomy plane is determined by relying on artificial experience is solved.

This application discloses a method and related equipment for evaluating the smoothness of in-vehicle infotainment systems, relating to the field of vehicle testing technology. The method includes: acquiring a recorded video stream of the in-vehicle interaction process of a target vehicle; parsing and processing the recorded video stream to obtain temporal data of the visual features of the in-vehicle infotainment system during the interaction process; determining quantitative information on the smoothness of the target in-vehicle infotainment system based on the temporal data of the visual features; and generating a smoothness score characterizing the smoothness of the in-vehicle infotainment system based on touch response latency, animation frame dropping features, and stuttering features. This application, by parsing and extracting temporal data of the visual features from the recorded video stream of the in-vehicle interaction process, quantifying touch response latency, animation frame dropping features, and stuttering features, and generating a unified smoothness score, can achieve an objective, detailed, and comprehensive evaluation of the smoothness of the in-vehicle infotainment system.

The invention discloses a voiceprint detection-based upender fault detection method and system. The method comprises the following steps of: acquiring a sound signal in an operation process of an upender and preprocessing the sound signal; performing framing and fast Fourier transform to obtain frequency domain spectrum data; obtaining a Mel spectrum through a Mel filter bank, performing logarithmic operation on the Mel spectrum to obtain a logarithmic Mel spectrum, and extracting voiceprint features; performing normalization processing and splicing to obtain a voiceprint feature sequence to be detected; establishing a normal voiceprint model and a fault voiceprint model to form a voiceprint model library; using the improved RealNVP model to output a matching result with the voiceprint model library, and obtaining a running state category result; according to the invention, the operation state monitoring and fault identification of the upender are realized, and the stability and accuracy of fault detection are improved.

The invention provides a parameterization calculation method for a top cover modal and a pitch diameter of a water turbine, and belongs to the technical field of hydraulic mechanical structure dynamics and simulation automation. The method comprises the steps of parameter input, parametric modeling, automatic simulation control, pitch diameter identification and analysis and result output: after a parameter set is input, constructing a parametric modeling module based on Python and ANSYS Spaceclaim, and automatically generating a three-dimensional geometric model containing a basic panel, a rib plate and a connecting hole; an automatic simulation control module is constructed based on Python and ANSYS Workbench, and full-process automatic simulation is completed to obtain a modal analysis result; pitch diameter characteristic parameters are automatically recognized through a least square discrete Fourier transform algorithm of non-equiangular sampling and confidence degree judgment; and outputting results to form a standardized database. According to the method, automation and quantification of the whole process are achieved, modeling and simulation efficiency is improved, manual misjudgment is avoided, the method is suitable for different types of water turbine top covers, and reliable data support is provided for structural optimization and resonance risk assessment.

The invention discloses an intelligent detection method and system for garment quality inspection, and relates to the technical field of computer vision and intelligent manufacturing. The method comprises the following steps: carrying out pixel-level feature analysis on two-dimensional image data, identifying a sewing line and a printing area, and mapping the sewing line and the printing area to a unified space coordinate system; reconstructing the three-dimensional surface form of the garment based on a stereoscopic vision algorithm, and calculating the dimensional deviation of key parts; converting the spectral data into a CIELAB color space, and carrying out optical distortion correction on local chromatic aberration in combination with a three-dimensional curvature; and under a unified space coordinate system, performing correlation analysis on the stitches, the dimensional deviation and the corrected space distribution, identifying a composite defect which cannot be judged by a single defect, generating a correlation defect identifier, and finally forming a quality report. The technical problems that in the prior art, local chromatic aberration is easily influenced by three-dimensional curved surface deformation and optical distortion of ready-made clothes, information such as dimensional deviation, sewing and printing defects and the local chromatic aberration is isolated, comprehensive correlation analysis is lacked, and consequently the detection accuracy is insufficient are solved.

The invention is applicable to the technical field of clinical examination and auxiliary diagnosis, and provides an extreme behavior risk auxiliary diagnosis biomarker combination, a kit and a detection method, the biomarker combination is composed of IL-4, IL-12 and IFN gamma, and the extreme behavior risk can be objectively identified by detecting the expression level of the combination in peripheral blood of a subject. The matched kit comprises specific antibodies aiming at the three markers, a standard substance, a buffer solution and other reagents, and according to the standardized detection method, through peripheral blood sample treatment, incubation, fluorescent staining, flow detection and result analysis, precise evaluation is achieved in combination with a clear judgment threshold value. According to the method, the defect that suicide risk assessment depends on a subjective scale and doctor experience in the prior art is overcome, the operation is convenient, the result is objective, the combined detection AUC of the suicide risk assessment, the subjective scale and the doctor experience can reach 0.726, a reliable extreme behavior risk auxiliary diagnosis means is provided for clinic, and the method is particularly suitable for risk identification of depression patients and has important clinical application value and conversion prospect.

The invention relates to the technical field of fan control and discloses a fan control method and system based on sensor data analysis and a storage medium, and the method comprises the steps that fan control data are obtained through an input module, and rotating speed data are extracted and displayed; pWM signals are calculated according to the rotating speed data and the fan attribute data, and the rotating speed of the fan is controlled; a speed sensor collects feedback signals and converts the feedback signals into rotating speed feedback data; matching the rotating speed feedback data with the rotating speed data, if not, displaying early warning, otherwise, displaying the feedback data; and calculating a differential absolute value, and adjusting an early warning flicker frequency or giving an alarm according to comparison with a first reference value. The system comprises a control module, a power supply module, an input module, a fan module, a driving module, a display module and a sound module. The storage medium stores computer programs and implements the method steps when being executed. According to the method, closed-loop control and self-adaptive adjustment of the fan are achieved, the rotating speed and heat dissipation requirements are dynamically matched, and the equipment operation stability is improved.

This invention discloses a method for autonomously constructing an evolvable knowledge graph by integrating a multimodal large-scale model, relating to the fields of artificial intelligence and knowledge graph technology. The method includes: collecting raw multimodal data from text, images, audio, and structured tables; using a pre-trained multimodal understanding large-scale model to perform unified semantic encoding on the raw multimodal data, generating modality-independent deep feature vectors to form an initial multimodal feature pool; performing cross-modal clustering analysis on the vectors in the feature pool, grouping semantically similar vectors into the same feature cluster, with each feature cluster defined as a candidate knowledge concept node; constructing an initial concept relationship network based on the co-occurrence relationship and feature similarity between candidate concept nodes; iteratively optimizing and evolving the network according to preset graph quality evaluation indicators, outputting the final evolvable knowledge graph. This invention achieves the autonomous and unified construction and evolution of a knowledge graph from multimodal data.

The invention discloses an integrated tree model-based intelligent evaluation method for the construction quality of a fabricated prefabricated beam bridge, and belongs to the field of bridge engineering quality evaluation, and the method comprises the steps of constructing a three-level quality evaluation index system of beam bridge construction; according to the actual measurement data of the second-level indexes, obtaining standardized characteristic data through mixed index preprocessing; a random forest model, an XGBoost model and a LightGBM model are constructed, and model training and hyper-parameter optimization are carried out; presetting model performance evaluation indexes, and selecting one model with the optimal comprehensive performance from the three candidate models as a construction quality evaluation model; and obtaining a construction quality grade evaluation result according to the construction quality evaluation model and the standardized feature data of the to-be-evaluated T-beam bridge. According to the method, intelligent evaluation of the construction quality of the fabricated T-beam bridge is realized, the limitation of traditional subjective weighting is eliminated, and the objectivity and accuracy of evaluation are remarkably improved by learning a historical data rule and continuously optimizing.

This invention provides a perception fusion arbitration method and system based on vehicle-to-everything (V2X) communication. The method includes: acquiring a ground truth model of the perception system for the road environment and meteorological information; acquiring perception information and data quality parameters from each sensor in the vehicle-mounted perception system; retrieving the influence coefficients of each sensor corresponding to the meteorological information and calculating the perception quality score of each sensor based on the data quality parameters to determine the optimal sensor; selecting candidate arbitration ratios from a pre-set perception fusion arbitration ratio case library; performing simulated fusion calculations on the perception information; comparing the matching degree of each fusion result with the ground truth model of the perception system to determine the optimal arbitration ratio; and sending the result to the vehicle controller. This invention achieves adaptive output of the optimal vehicle-mounted sensor fusion weight ratio according to the specific meteorological environment, significantly reducing the perception misidentification rate in adverse environments such as rain, snow, fog, and sandstorms, ensuring the perception prediction accuracy of the autonomous driving system in all weather conditions.

The embodiment of the invention provides an image retrieval method, device and equipment for target image information. The method comprises the following steps: acquiring to-be-retrieved target image information; analyzing and extracting the target image information to obtain target image feature information; matching the target image feature information in a preset image data structured index database, and retrieving to obtain a retrieval result containing matched target image data and structured description information associated with the target image data; outputting a retrieval result; wherein the image data structured index database is obtained through the following processes: obtaining multi-modal original data containing images, videos and text descriptions of the same target object; performing content analysis and feature extraction on the multi-modal original data to obtain corresponding structured description information; and storing the structured description information as an index structure supporting feature-based matching retrieval according to a preset storage format. According to the embodiment of the invention, the deep semantic content of the image can be efficiently understood and accurately matched.

The invention belongs to the technical field of service intelligent evaluation, and particularly provides a service provider SLA evaluation dynamic service model implementation method and system, and the method mainly comprises the steps: obtaining the SLA evaluation source data of a service provider, the SLA evaluation source data comprises operator SLA data, enterprise end-to-end APM data, third-party network quality data, and dependency link probe data between service providers; the method comprises the following steps: by taking service providers as nodes, setting a credibility weight for each node according to a preset rule, determining directed edges between the nodes according to a preset dependency relationship between the service providers, and determining a connection weight of the directed edges according to dependency link probe data; according to the method, dynamic accurate evaluation under multi-dimensional data fusion is realized, the objectivity and credibility of an SLA achievement rate evaluation result are improved, and reliable decision support is provided for enterprises to screen cloud service providers and optimize service deployment.

This invention discloses a method and system for diagnosing and assessing teacher competence based on multimodal data fusion, applied in the field of data analysis. The method includes acquiring teaching video data of the target teacher and its corresponding lesson plan text data; then adaptively segmenting the lesson plan text into multiple text blocks, with the segmentation boundaries determined based on semantic density distribution; fusing corresponding sentiment enhancement vectors into each text block and extracting audio track prosodic features from the teaching video; establishing a precise correspondence between each text block and audio track segment using spatiotemporal alignment technology, and then calculating the first and second matching degrees; adjusting the contribution weight of semantic density to each matching degree to generate the final diagnostic assessment result of teacher teaching competence. The teacher competence diagnostic assessment method based on multimodal data fusion provided by this invention effectively improves the objectivity, granularity, and educational guidance value of teacher teaching competence assessment.

The application provides a training system for kidney stone minimally invasive surgery, a training method and a manufacturing method of a kidney model. The training system comprises a kidney model, an image acquisition device, a flexible piezoresistive sensor, a host computer and a display device. The kidney model is internally provided with a stone and a kidney pelvis filled with water. The image acquisition device is arranged at one end of a surgical instrument, used to enter the kidney model with the surgical instrument and acquire an intrarenal image. The flexible piezoresistive sensor is attached to the inner wall of the kidney pelvis near the abdominal side, used to generate an electrical signal according to the water pressure data in the kidney pelvis when the surgical instrument enters the kidney model. The host computer is used to analyze the electrical signal to obtain an intrarenal pressure parameter. The display device is used to perform a training task of the target level kidney stone minimally invasive surgery, obtain a position parameter of the surgical instrument in the kidney model according to the intrarenal image, and display the intrarenal pressure parameter and the position parameter in real time, so that a user operates the stone with the surgical instrument and evaluates the operation.

This invention discloses a method and system for identifying urban decline spaces, belonging to the field of urban planning technology. The method includes: S1. Acquiring population grid data and building area grid data of a target area for multiple consecutive years within a time interval; S2. Performing spatial alignment and standardization processing on the population grid data and building area grid data to form a standardized annual spatial database; S3. Removing grid units in the annual spatial database that do not possess effective urban activity characteristics to obtain a set of effective urban spatial grids; S4. Performing time series analysis on the effective urban spatial grid set to determine urban decline space grids; S5. Using a spatial clustering algorithm to cluster the determined urban decline space grids, dividing the urban decline space into continuous urban decline space and scattered urban decline space. This invention achieves automatic identification and classification of continuous and scattered urban decline spaces by analyzing the population and building area change trends over multiple consecutive years.

The invention discloses a method and system for detecting the internal quality of a polyethylene pipeline hot-melt welding joint, and belongs to the technical field of pipeline quality detection.The method comprises the following steps that before a tensile test is carried out, ultrasonic quality detection is carried out on a casual inspection joint of a polyethylene pipeline set to be detected; dynamically determining an initial tensile rate based on the material grade and the material attribute parameter of the to-be-tested polyethylene pipeline group, and executing a first tensile test at the initial tensile rate; iteratively and dynamically adjusting the tensile rate of the tensile test of the next casual inspection joint based on the tensile test result of the previous casual inspection joint until the tensile test of each casual inspection joint is completed; dynamically executing fracture quality detection based on the fracture position and the fracture characteristic parameter of each spot check joint to obtain a fracture quality detection result of each first joint; and executing internal quality comprehensive detection based on the ultrasonic quality detection result, the fracture quality detection result and the tensile test result of each first joint.

The invention is suitable for the technical field of crossing of computer vision, artificial intelligence and sports science, and provides a tennis posture evaluation system based on multi-modal data fusion, which comprises a three-dimensional posture extraction module, an action recognition module, an index calculation module and a natural language evaluation generation module, the three-dimensional posture extraction module is used for extracting a human body three-dimensional key point sequence from a monocular video according to an STCFormer model; the action recognition module is used for performing standardization processing, Bi-LSTM network processing and full-connection classification network processing on the human body three-dimensional key point sequence to obtain tennis action types; the index calculation module is used for calculating biomechanical parameters according to the action type and the human body three-dimensional key point sequence; and the natural language evaluation generation module is used for inputting the action type and the biomechanical parameters into a preset large language model to generate feedback information in a natural language form. Therefore, end-to-end automatic processing from original video input to final professional evaluation report generation is realized, and objectivity and accuracy of evaluation results are improved.

This invention provides a method and system for accurate tumor segmentation in CT images, relating to the field of image processing technology. The method includes: determining the region to be identified in a CT image containing a tumor using an image segmentation model; determining the boundary line, center position, and nearest reference pixels of the region to be identified, along with their probability information; and then selecting correction pixels from the nearest reference pixels to obtain a correction region, thereby updating the trained image segmentation model. According to this invention, after obtaining the region to be identified in the CT image of each slice using the image segmentation model, the boundary line of the region to be identified can be mutually verified based on the nearest pixels on the boundary line and the pixels of adjacent slices. This allows for the selection of pixels that better represent the tumor edge from the nearest pixels on the boundary line, thereby achieving more accurate segmentation of the region containing the tumor.