46 results about "Character analysis" patented technology

The invention relates to the technical field of soybean plant information analysis, in particular to a soybean whole plant character analysis method based on three-dimensional point cloud. Comprising the following steps: carrying out collection, labeling and standardized pretreatment on three-dimensional point clouds by adopting a soybean pod state joint labeling method based on the three-dimensional point clouds; an improved SoftGroup multi-task learning model is constructed, all the modules work cooperatively according to preset logic, the three-dimensional point cloud of the single plant of soybean serves as input, and target task result output is achieved through point cloud feature extraction and instance clustering; performing multi-task joint training on the improved SoftGroup multi-task learning model, preprocessing the three-dimensional point cloud of the soybean plant to be tested, inputting the preprocessed three-dimensional point cloud into the trained model, performing multi-task reasoning, correcting geometric parameters through PCA fine processing, and counting the pod bearing number; removing pod point cloud from the single-plant soybean three-dimensional point cloud to obtain plant main body point cloud; and extracting a plant skeleton from the plant main body point cloud, and obtaining character data of the plant skeleton.

The invention discloses a mushroom yield estimation method based on three-dimensional reconstruction lossless phenotype parameter extraction, belongs to the technical field of agricultural informatization and intelligentization, and solves the problem of low mushroom yield estimation accuracy. The method comprises the following steps: performing point cloud three-dimensional reconstruction on shiitake mushrooms by using a region of interest to generate dense point cloud data; preprocessing the dense point cloud data; based on an improved CP-PointNet + + model and a clustering algorithm, segmenting mushroom point cloud, extracting multi-dimensional key phenotypic parameters of pileus diameter, thickness and stipe height, and covering main features of mushroom phenotypic information; the improved PointNet + + network comprises the following steps: adding a CBAM module to an MLP layer of the PointNet + + network, and replacing common convolution with partial convolution PConv; and taking the phenotypic parameters of the shiitake mushrooms as input variables of the neural network model, and predicting the shiitake mushroom yield. The method is suitable for phenotypic character analysis and breeding research of edible mushrooms such as shiitake mushrooms and the like.

The invention discloses a field wheat three-dimensional character analysis method based on unmanned aerial vehicle multi-view three-dimensional point cloud, and the method comprises the following steps: S1, shooting a multi-view image and carrying out the three-dimensional reconstruction, and obtaining an original point cloud; performing interpolation segmentation and secondary segmentation, and outputting a plurality of cell point clouds; s2, performing data enhancement, starting model training, and obtaining each 3D bounding box; s3, extracting point cloud data of each planting row from each 3D bounding box by using a row segmentation algorithm, and calculating each static phenotype parameter; and S4, calculating five dynamic phenotypic parameters of the field wheat. According to the invention, based on the 3D wheat plot detection network and the row segmentation algorithm, the point cloud data and the 3D bounding box of the wheat are rapidly extracted, and accurate monitoring and accurate segmentation of the wheat are realized; based on accurate analysis of static phenotypic parameters, a new system of dynamic phenotypic parameters is provided, and based on the dynamic phenotypic parameters, the growth vigor and yield of wheat can be effectively predicted.

The invention discloses a character analysis method based on artificial intelligence. The method comprises the following steps: obtaining user dialogue content; a plurality of artificial intelligence models are constructed, and the plurality of artificial intelligence models comprise a management model and a plurality of scoring models; dividing the character into a plurality of dimensions, and distributing one dimension for each scoring model; inputting the user dialogue content into each scoring model, scoring the user dialogue content by each scoring model according to the distributed dimension, and outputting scoring results of multiple dimensions; and inputting the scoring results of the multiple dimensions into the management model, processing the scoring results of the multiple dimensions through the management model, and outputting a multi-dimensional character scoring report. According to the method, the multiple character dimensions are analyzed through the multiple artificial intelligence scoring models, the scoring report is output through the artificial intelligence management model, and the multi-dimensional character analysis result of the user can be accurately obtained.

The invention relates to an engineering image-text cross-modal automatic reconstruction method based on a large model. For a gas path diagram of integrated circuit manufacturing equipment, firstly, all characters in the diagram are analyzed by adopting a PDF analysis method, and are written into a character analysis result file; and then identifying an image main region through a YOLOv5 training model, writing the image main region into a main region identification result file, identifying various devices through the YOLOv5 training model, and writing the devices into a device identification result file. And obtaining a main area of the engineering drawing through the coverage function, filtering out characters and devices in the main area, recognizing a straight line through an LSD algorithm, and writing the straight line into a straight line recognition result file. And integrating all the analysis result files to form an input analysis file of the engineering drawing multi-modal large model. Advanced technologies such as artificial intelligence, PDF analysis and line segment recognition are comprehensively applied, sensing and data analysis of IC manufacturing equipment gas path diagram information are achieved, and deep fusion and reconstruction of multi-source engineering information are achieved.

The invention discloses a pea whole genome 20K SNP (Single Nucleotide Polymorphism) liquid phase breeding chip and application thereof, the liquid phase breeding chip comprises 21 and 659 SNP loci on a pea whole genome, the SNP loci comprise published 235 reliable functional loci obviously related to 57 characters, and examples for pea sample genetic typing are provided. The chip can be widely applied to important character analysis, germplasm resource genetic diversity analysis, variety identification analysis, auxiliary selective breeding, population structure analysis, heredity and evolution analysis, genetic relationship identification, whole genome association analysis or genome selection of peas, and is helpful for improving the pea breeding efficiency; the innovation and improvement of pea varieties are promoted.

The invention discloses a molecular marker Site1773 closely linked with a melon leaf color yellowing character and application of the molecular marker Site1773, and belongs to the field of plant molecular genetic breeding research. The molecular marker is used for detecting leaf yellowing characters in a plurality of natural muskmelon populations, DNA (deoxyribonucleic acid) of a material to be selected is used as a template, a primer pair of the molecular marker Site1773 is used for PCR (polymerase chain reaction) amplification, an amplification product is subjected to polyacrylamide gel electrophoresis, field character analysis is combined, and the identification accuracy rate of the molecular marker in the seedling stage is 100%. The molecular marker has very important value in muskmelon production practice and breeding. The operation method is simple, convenient, high in stability, rapid and accurate, and a novel auxiliary selection method is provided for molecular breeding of muskmelons.

The invention discloses an AI project management optimization system based on artificial intelligence, and relates to the technical field of project management, and the system comprises a project optimization module, a quality evaluation module, a character analysis module, a project characteristic analysis module and a personality matching module, and also comprises a completion degree division module and a reward adjustment module. The system has the advantages that the scheme can be modified through the project characteristic analysis module in combination with project directions skilled by different character traits, reasonable distribution of project tasks is realized according to the character traits of employees, the working efficiency is improved, the character traits lacked in the traits distribution scheme can be better analyzed by utilizing the project characteristic analysis module, and the project distribution efficiency is improved. According to the scheme, the most suitable employees are distributed for the project, the personality advantages of the employees are fully exerted, the personality matching module analyzes the execution time of different sub-project schemes and marks the matched employees, the employees are prevented from being repeatedly marked, and reasonable utilization of human resources is ensured.

The invention discloses an AI psychological counseling method and system for generating an emotional map and a differentiation report, and relates to the technical field of artificial intelligence and psychology crossing. The invention discloses an AI psychological counseling method and system for generating an emotional map and a differentiated report. Through interaction of voice and characters, a visual emotional map is generated, personalized action suggestions are generated, and a visitor report or a psychological counselor report is generated. According to the method, a visual emotional map is generated through voice and character analysis, changes in the emotional map can be seen more visually, meanwhile, a proper psychological AI model is adapted, personalized action suggestions and corresponding related reports are generated, fine emotional fluctuations can be effectively captured through the accurate voice and character capturing capacity, and therefore the emotional effect is improved. A multi-dimensional emotion analysis model is arranged in the system, emotion fluctuation is monitored in real time, a detailed emotion change trend chart is generated, and the scientific basis is provided for psychological counseling.

The invention discloses an intelligent question answering method and device based on character characters, equipment and a medium, and belongs to the field of artificial intelligence. The method comprises the steps that information extraction is conducted on user questions, and keywords are obtained; searching data of a corresponding user according to the keyword to obtain associated data; wherein the associated data comprises text associated data, image associated data and video associated data; performing multi-source data feature extraction based on the type of the associated data to obtain a first character character feature; performing MBT I character analysis according to the first character character characteristics to obtain second character character characteristics; and generating an answer according to the user question, the keyword, the first character character feature and the second character character feature, and outputting an answer text of the user question. Therefore, by implementing the method and the device, accurate answers more fitting the personality of the user can be generated.

The application discloses a kind of based on molecular marker clustering analysis's cotton hybrid breeding combination screening method, the screening method includes: step S1: using multi-traits related molecular marker to the gene typing experiment of test cotton variety, data collection and arrangement are carried out;Step S2: excellent allele frequency calculation and feature matrix construction;Step S3: data standardization and principal component analysis dimension reduction;Step S4: optimal cluster number selection and genetic clustering;Step S5: each population character analysis;Step S6: heterosis potential score and combination screening.The technical problem that present cotton breeding parent selection lacks multi-traits comprehensive quantitative evaluation is solved, and the data of breeding decision-making and intelligentization are realized.

The invention discloses a 3D online self-service packaging system based on artificial intelligence, which belongs to the technical field of packaging design, and comprises a material storage module used for establishing a material library and storing component element data of packaging materials; the character input module is used for inputting character information required by packaging; the character analysis module is used for analyzing the character information to obtain an evaluation value; the packaging material generation module is used for selecting a material generation mode according to the evaluation value and generating a packaging material set by utilizing the selected material generation mode; and the material editing module is used for editing and downloading the component element data of the packaging materials selected in the packaging material set. By integrating the artificial intelligence technology, the material library resources and data analysis, the editable and downloadable packaging material source file meeting the requirement can be automatically generated according to the text information input by the user, and an efficient, flexible and personalized 3D online self-service packaging solution is provided for the user.

The embodiment of the invention provides a photo volume generation method and device based on a large model, and the method comprises the steps: describing the contents of all reconnaissance images in a preset range based on a multi-modal large model according to a first cue word, and generating a detail title of each reconnaissance image; carrying out character analysis on the detail title of each survey image according to a second cue word based on a large language model to obtain a spatial hierarchy corresponding to the detail title; according to the investigation images of different spatial levels, feature extraction is carried out on the investigation images based on a diffusion model network, and duplicate removal is carried out on the same view angle images of the same spatial level; on the basis of a diffusion model network, sequentially segmenting each survey image from the survey image set of the uppermost spatial hierarchy, searching for the most similar survey image in the next spatial hierarchy, and performing spatial matching; based on a result of the spatial matching, a photo volume from a complete spatial hierarchy is generated.

The invention discloses a Tujia brocade culture genetic map-based virtual digital human role precise modeling system and method, and relates to the technical field of virtual digital human roles, and the system comprises a data acquisition module, a virtual digital human role creation module, a virtual digital human role analysis module and a feedback judgment module. The method comprises the following steps: establishing a target according to a virtual digital human role uploaded by a user, evaluating a scene adaptation index of a demand virtual digital human role model of the user, expanding culture influence, operating the established demand virtual digital human role model of the user, judging whether the demand virtual digital human role model of the user is adaptive or not, and if yes, executing the operation of the user. If the model is not matched with the scene, regeneration is carried out, the requirement integrating degree of the model and the actual use scene is improved, the problems of abnormal functions or poor experience and the like caused by the fact that the model is not matched with the scene are avoided, the working efficiency is improved, and inheritance and propagation of Tujia brocade culture are promoted.

The invention relates to the technical field of character recognition, in particular to a method and device for recognizing characters in a code spraying image in real time, character scene types in the code spraying image are analyzed, character analysis modes matched with the character scene types are selected according to the different character scene types, character recognition is carried out on the code spraying image, and the character recognition efficiency is improved. And for character scenes such as scattered character distribution and short texts, identifying a character identification category of each character in the code spraying image, and for character scenes such as continuous text lines and long texts, identifying a character identification position of each character in the code spraying image, so as to obtain a character identification result matched with the character mode of each character in the code spraying image. The character recognition accuracy and efficiency are improved, the corresponding character recognition results are analyzed based on different character analysis modes to obtain the code spraying quality of the code spraying image, the real-time detection accuracy of the code spraying quality of the code spraying image is improved, code spraying parameters can be adjusted and optimized in a self-adaptive mode, and then the code spraying effect is improved.

Methods, computer-readable media, software, and career planning system may receive inputs from a user in response to questions related to personality and may provide outputs related to preferences for schooling and other career options, such as courses, colleges, universities, programs, majors, careers, jobs, and / or companies. The personality of the user may be broken into four (or other numbers) different pillars, life vectors, and / or personality characteristics and the user may be provided a score in each of the pillars, life vectors, and / or personality characteristics based on the responses to the questions. These scores for each of the pillars, life vectors, and / or personality characteristics may be then matched to various schooling and career option recommendations for the user.

The invention discloses a drug safety risk assessment system, and belongs to the technical field of drug safety risk assessment, and the system comprises a drug classification module which is used for classifying to-be-assessed drugs; the character analysis module is used for analyzing to-be-evaluated drug characters; the detection method evaluation module is used for providing the most suitable evaluation method for the medicine to be evaluated; the risk assessment module is used for performing risk assessment on the to-be-assessed medicine; according to the invention, to-be-assessed drugs are classified through the drug classification module, the traits of the to-be-assessed drugs are analyzed through the traits analysis module, the detection method assessment module provides a most suitable assessment method for the to-be-assessed drugs, and the risk assessment module carries out risk assessment on the to-be-assessed drugs. Therefore, the corresponding risk assessment scheme can be quickly matched to comprehensively assess the safety risk of the medicine, the safety problem of the medicine can be found and prevented in advance, and the safety and effectiveness of medicine use of a patient can be guaranteed.

The present application relates to the field of image processing, and more particularly to a dish visual processing detection system, comprising: a collection and analysis module, configured to perform quality detection on a randomly selected target detection product and key label image collection, and to detect a collection quality coefficient of each character image in the key label image, and determine the category of the character image according to the collection quality coefficient; a data analysis module, configured to determine a processing mode according to an abnormal character proportion; a secondary processing module, configured to determine a to-be-adjusted character region and perform region adjustment, and determine an image processing mode according to a contrast reference value and a proportion of a reflective region; and a character analysis module, configured to determine a character recognition mode according to an abnormal key coefficient, so that the accuracy of the information recognition result of the key label image with abnormal character images is improved, and the degree of dependence on personnel recognition is reduced.

The invention relates to the technical field of printing character defect detection, in particular to a printing character defect detection device based on a mechanical scanning mechanism, and is used for solving the problems that an existing printing character defect detection mode is low in detection efficiency, high in false detection rate and difficult to meet complex and changeable printing environments and high-quality detection requirements. The device comprises the following modules: a mechanical scanning mechanism, a scanning mechanism control module, a character analysis module, a character defect detection module and a character defect evaluation module, according to the device, the adaptive adjustment of different printed matters is realized by selecting the scanning rate, the accurate acquisition of printed characters is improved, and the defect detection accuracy of the printed characters is improved; according to the device, potential defects can be efficiently and accurately identified by utilizing the defect measurement coefficient and the abnormity early warning coefficient, so that effective detection of various types of printing character defects is realized, and an important basis is provided for quality control of printed matters.

The invention discloses a handheld crop character detection system, and relates to the technical field of agriculture. The system comprises a waistband, a camera rod, a platform, a camera, a bracket, a display, a protective shell, a power supply and a control panel, a ubuntu operating system is embedded in the control panel, and an improved YOLOv8 target detection algorithm is arranged on the operating system; the improvement is that a Faster Net network is utilized to replace a backbone network in an original model; adding an EMA attention mechanism in the neck network; plant character pictures are collected through a camera to form a data set, and crop character analysis is carried out on the data set through an improved YOLOv8 target detection algorithm. The method is convenient to wear and carry, and compared with a traditional subjective crop character judgment basis, the method has the advantages of being accurate and better in robustness.

The application relates to a large scene character behavior analysis method, system, device and storage medium, and relates to the field of artificial intelligence. The method comprises the following steps: calibrating scene areas of a plurality of long-range cameras and recording a plurality of area calibration information, wherein the area calibration information comprises coverage areas of the plurality of long-range cameras and object information and object coordinates in the coverage areas; collecting a plurality of scene data by using the plurality of long-range cameras, and synchronizing the plurality of scene data in time; tracking character trajectories in the plurality of scene data by using a pedestrian re-identification model to obtain a plurality of area stay times and a plurality of area images corresponding to the plurality of area stay times; performing multi-modal analysis on the plurality of area images to obtain a plurality of character analysis results; and fusing the plurality of character analysis results to obtain a character analysis comprehensive result. The technical effect of the application is to improve the accuracy of character behavior analysis in a large scene.

The invention provides a dialogue content-based user character analysis method and system, and relates to the field of text content understanding in natural language processing, and the specific scheme comprises the following steps: obtaining the dialogue content of a to-be-analyzed user; extracting emotional features and emotional regulation features in the dialogue content by using a large language model to form a user feature vector, retrieving a most similar sample from a historical dialogue data reference library by using the user feature vector, and generating a thinking chain of the most similar sample; performing user character classification based on dialogue contents, most similar samples and thinking chains of the most similar samples; the method is inspired by psychological research results, the emotion features and the emotion regulation features are introduced in the character detection process, understanding of the model on characters is enhanced, and the accuracy and robustness of model character detection are improved.

The invention relates to a character character analysis method and device, electronic equipment and a medium, and relates to the field of natural language processing, and the method comprises the steps: obtaining chat records corresponding to a target object and a plurality of dialogues, and determining the preference character of the target object based on all chat records, performing tone recognition on statements of the target object and the dialogue person in each chat record to obtain a first emotion of the target object and a second emotion of the dialogue person corresponding to each chat record, and determining a preference emotion of the target object based on the first emotion and the second emotion, and determining a character feature value of the target object based on the preference emotion and the preference character, and determining a character portrait of the target object based on the feature value. According to the method, more specific, detailed and accurate character description can be obtained according to the text about the character.

The invention relates to a text analysis method, device and equipment, a medium and a vehicle. The method comprises the following steps: receiving a plurality of to-be-processed texts and question statements corresponding to the to-be-processed texts; analyzing semantic relevancy between the to-be-processed texts and the question sentences to obtain semantic relevancy degrees between the to-be-processed texts and the question sentences; sorting the to-be-processed texts according to a sequence of semantic association degrees from large to small to obtain a text sequence; starting from the starting text of the text sequence, the corresponding to-be-processed text smaller than or equal to a preset character number is screened as a target text, and the preset character number is smaller than or equal to the maximum processable character number of the language processing model; the target text and the question statement are input into the language processing model, language analysis is performed based on the language processing model, and the answer statement corresponding to the question statement is output, so that the number of characters needing to be analyzed by the language processing model can be reduced, and the character analysis efficiency and the working efficiency of the language processing model are improved.

The application provides a state machine-based streaming data analysis method, system, device and storage medium. The method comprises: receiving packet streaming data; initializing a state machine and performing character-by-character analysis on the streaming data; when the analysis state of the state machine is a text state, if the analyzed character is a label start symbol, switching the analysis state of the state machine to a label state; when the analysis state of the state machine is the label state, storing the analyzed character in a label buffer until the analyzed character is a label end symbol, ending the character analysis of the current streaming data; querying a predefined configuration mapping table based on the string content of the label buffer to determine a label type; performing a data block operation based on the label type and dynamically appending the recognized non-label character to the current active data block. The application improves the accurate analysis rate of streaming data and the multiplicity and maintainability of the scheme.

A multi-dimensional context and hierarchical authorization dynamic character analysis system and method belong to the field of enterprise-level data authority management, and the method comprises the following steps: a receiving and recognition module dynamically recognizes a time template, a user context template, a function template, a hierarchical authorization template and a parameterized template type through a regular expression; the recursion decoding module avoids infinite recursion and processes any hierarchical nested template; the hierarchical authorization processing module calls a data permission interface to dynamically generate an SQL fragment containing an organization identifier; the parameterization processing module extracts attribute values of an external business object set through a reflection mechanism, and secondary recursive decoding is triggered after the attribute values are assembled into list format character strings. According to the method, dynamic fusion of user, time and organization triple constraints can be realized, single configuration of complex business rules is supported, a new template type can be expanded without hard code modification, a decoding process is traced through a security white list control function call and auditing module, and the flexibility of a permission system and the batch business adaptation capability can be remarkably improved.

The invention relates to the technical field of employment planning, in particular to an AI and character analysis-based occupational planning method and a terminal, which can efficiently screen massive occupational information by issuing character questionnaires, generating character feature vectors and calling an occupational feature library constructed by expert annotations and machine learning. The modal difference between characters and occupational characteristics is eliminated through cross-modal alignment, dynamic attention weights are generated to highlight occupational key character requirements, recommendation is performed according to weighted similarity, the adaptation degree of occupations and user characteristics can be greatly improved, effective occupational recommendation conforming to the user characteristics is provided, short-term demission caused by inconsistent characters is reduced, and the user experience is improved. Not only is job hunting time cost of students reduced, but also recruitment burden of enterprises is reduced.

A computer-implemented method, according to one embodiment, includes receiving, from a user device, a request for determining a final confidence score for an account, and determining a plurality of confidence parameter scores using information associated with the account. A first of the confidence parameter scores is determined based on an analysis of a structure of the account, a second of the confidence parameter scores is determined based on a character analysis of at least the account, and a third of the confidence parameter scores is determined based on an exposure of the account. The method further includes using the determined confidence parameter scores to determine the final confidence score for the account. The determined final confidence score is applied to mitigate fraud.

The invention relates to an abnormal mail detection method and device, computer equipment and a storage medium. The method comprises the following steps: carrying out text anomaly analysis on sending information in a to-be-detected mail by utilizing a preset big language text analysis model, and determining a text anomaly probability of the to-be-detected mail; the big language character analysis model is obtained by performing fine tuning training through an instruction fine tuning data set; the instruction fine tuning data set comprises a mail title, a mail text and a mail abnormal probability; under the condition that the character abnormal probability is greater than a preset probability threshold value, skipping according to an external skipping entry in the to-be-detected mail, and obtaining webpage skipping information corresponding to the external skipping entry; and based on the sending information and the webpage jump information in the to-be-detected mail, performing jump anomaly detection on the external jump entry in the to-be-detected mail to obtain an anomaly detection result of the to-be-detected mail. By adopting the method, mail anomaly detection can be accurately carried out.

The invention relates to the technical field of computer vision, and discloses a cartoon role analysis method based on space learning and structure modeling, which is used for cartoon role analysis based on space learning and structure modeling. According to the method, the problems of low analysis accuracy of different cartoon roles and the like in the prior art are solved.