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58results about How to "Avoid manual labeling" patented technology
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Hand key point recognition model training method and device, recognition method and device
ActiveCN110163048AImprove training efficiencyImprove accuracyInput/output for user-computer interactionImage analysisPattern recognitionDimensional modeling
The invention discloses a hand key point recognition model training method and device and a recognition method and device, and belongs to the field of gesture recognition. The method comprises the following steps of: using a Cycle-GAN model to convert the sample virtual image into a simulation image, wherein the sample virtual image is an image generated by three-dimensional modeling, the samplevirtual image comprises key point coordinates corresponding to hand key points, and the simulation image is used for simulating an image collected under a real scene; extracting a hand image in the simulation image; and training a hand key point recognition model according to the hand image and the key point coordinates in the simulation image, the hand key point recognition model being used for outputting the hand key point coordinates of the hand in the real image according to the input real image. In the embodiment of the invention, the training sample is closer to the acquired real image,and the accuracy of gesture recognition on the real image by using the hand key point recognition model subsequently is higher.
Owner:TENCENT TECH (SHENZHEN) CO LTD
Semi-supervised automatic aspect extraction method and system based on domain information
ActiveCN103903164AAvoid Manual LabelingPerformanceSpecial data processing applicationsMarketingSemantic clusteringDocument preparation
The invention discloses a semi-supervised automatic aspect extraction method based on domain information. The semi-supervised automatic aspect extraction method comprises the steps of network information crawling, information pre-processing, keyword extraction, comment document recombination and fine-grit mark LDA learning. The invention further discloses a semi-supervised automatic aspect extraction system based on the domain information. The semi-supervised automatic aspect extraction system based on the domain information comprises a network information crawling module, an information pre-processing module, a keyword extraction module, a comment document recombination module and a fine-grit mark LDA learning module. By the adoption of the semi-supervised automatic aspect extraction method and system based on the domain information, all extracted aspects of a commodity are more clear and more definite, and the differences between the aspects are more clear; a generated aspect structure (order and content) generated through the semi-supervised automatic aspect extraction method and system can be kept consistent with a commodity aspect structure which is predefined in a seed word set, so that the semi-supervised automatic aspect extraction method and system have the advantages that semantic clustering can be conducted on different expressions used by a consumer for description of the same commodity aspect, and human interference can be reduced in the process of opinion mining of the commodity.
Owner:SOUTH CHINA UNIV OF TECH
Method for identifying text font in natural scene picture
ActiveCN108376244AImprove recognition accuracyLow costImage analysisCharacter and pattern recognitionPattern recognitionSynthesis methods
The invention discloses a method for identifying a text font in a natural scene picture. With a picture synthesis method, lots of natural scene pictures that are integrated with different font texts and are similar to real effects specifically are obtained; picture training is carried out to obtain a font identifying device and a text location device; more text pictures are located in an internetpicture by using the text location device; and on the basis of a migration learning method, learning is carried out in the pictures by using the font identifying device, so that the identification precision is improved. According to the invention, the high-quality training picture is synthesized automatically, so that manual marking needing lots of time and efforts is avoided and the cost is lowered substantially; with the font classification device, the high identification precision is realized. Besides, because of introduction of the migration learning method, the accuracy of the font classification device is enhanced by using lots of font-tag-free pictures.
Owner:PEKING UNIV
Generation method and device of word segmentation training set
ActiveCN104866472ARealize automatic generationShorten the timeSpecial data processing applicationsNoise reductionTraining set
The invention provides a generation method and device of a word segmentation training set. The generation method of the word segmentation training set comprises the following steps: obtaining training corpus, adopting different word segmentation devices to independently carry out word segmentation on different training corpuses to obtain word segmentation results corresponding to different word segmentation devices; dividing the word segmentation results into accurate matching word segmentation results and non accurate matching word segmentation results; and according to the word segmentation results, carrying out noise reduction processing on the non accurate matching word segmentation results to obtain the word segmentation training set. The method can lower time and cost for the generation of the word segmentation training set, is low in implementation cost and improves effect.
Owner:BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
Text processing method and device, computer readable storage medium and electronic equipment
ActiveCN111737476AHigh precisionImprove stabilityMachine learningNeural architecturesMulti-label classificationEngineering
The invention provides a text processing method and device, a computer storage medium and electronic equipment, and relates to the field of artificial intelligence. The method comprises the followingsteps: obtaining text to be processed, inputting the text to be processed into a multi-label classification model, wherein the multi-label classification model is obtained by training based on an unbalanced text sample set and an unbalanced attenuation loss function, the unbalanced text sample set is a text sample set in which the number of label positive samples and the number of label negative samples are unbalanced, and the unbalanced attenuation loss function comprises a first loss part, a second loss part and recall loss; performing attribute extraction on the to-be-processed text throughthe multi-label classification model to obtain a label corresponding to the to-be-processed text; and obtaining a corresponding entity from the to-be-processed text according to the label, and constructing a triad according to the label and the entity so as to update the knowledge graph according to the triad. According to the invention, the on-call rate of the text label can be improved and thecost is reduced.
Owner:TENCENT TECH (SHENZHEN) CO LTD
User query intention understanding method, system and computer terminal
InactiveCN108228820AStrong semantic feature expression abilityAvoid Manual LabelingSpecial data processing applicationsText database clustering/classificationDeep learningKnowledge base
The invention discloses a user query intention understanding method, system and computer terminal. The method comprises the steps that a seed concept of a predetermined intention domain is taken as astarting point, concepts and classification labels related to the domain in a knowledge base are crawled; according to the crawled concepts and classification labels, a concept link graph of the predetermined intention domain is established; the probability of nodes in the concept link graph belonging to the predetermined intention domain is calculated; a user query statement is acquired, the concept link graph is retrieved, if the user query statement covers concept nodes, the concepts are returned; if no, a deep learning model is used to calculate the similarity between the user query statement and each concept node, and the first K concepts most similar to the user query statement are returned; according to a returned result and the probability of the concept nodes belonging to the predetermined intention domain, the probability of the user query statement belonging to the predetermined intention domain is calculated, and compared with a predetermined threshold, it is judged whetheror not the user query statement belongs to the predetermined intention domain. The user query intention understanding method, system and computer terminal solve the problem of the concept feature coverage and semantic expression of the query statement.
Owner:厦门太迪智能科技有限公司
Short text opinion excavation method based on complementation corpus
ActiveCN106227768AOvercome ambiguityComprehensive and in-depth perspective miningWeb data indexingNatural language data processingPart of speechMicroblogging
The invention discloses a short text opinion excavation method based on complementation corpus, and belongs to attribute opinion excavation; the method comprises the following steps: firstly selecting training corpus from certain segment of weibo corpus, segmenting words, tagging part-of-speech, and selecting; tagging attribute words for training corpus according to opinion words; using part of speech tags as a characteristic training maximum entropy model; then, building a cross-corpus topic model according to weibo corpus and news corpus of certain event, combining the maximum entropy model to parse the topic to which the event belongs, and extracting corresponding attribute word distribution and opinion word distribution; finally, using an emotion classifier to carry out polarity analysis according to all opinion words of certain specific sharing topic or all opinion words of certain specific exclusive topic. The short text opinion excavation method can carry out attribute analysis and opinion excavation on certain public opinion event, has high effectiveness, robustness and usability, and can provide important application values on opinion excavation and public opinion monitoring fields.
Owner:NAT COMP NETWORK & INFORMATION SECURITY MANAGEMENT CENT
Unsupervised medical image segmentation method based on adversarial network
InactiveCN112734764AAvoid Manual LabelingQuality improvementImage enhancementImage analysisManual annotationData set
The invention relates to an unsupervised medical image segmentation method based on an adversarial network, belongs to medical care informatics, and particularly relates to the technical field of medical image segmentation. According to the technical scheme, the method comprises the following steps: firstly, randomly generating or utilizing a third-party data set to obtain a group of auxiliary masks according to shape prior information, and sending the auxiliary masks and an unlabeled training image into a cyclic consistency adversarial network to generate binary masks; and a discriminator based on variational self-encoding and a generator correction module based on discriminator feedback are utilized to improve the quality of the binary mask. And after the binary mask of the training image is obtained, iterative training is performed by using a noise weighted Dice loss function, so that a final high-precision segmentation model can be obtained. According to the method, the problem that the convolutional neural network needs a large number of manual annotations in the training process of medical image segmentation can be solved, the problems of low performance, poor robustness and the like of an unsupervised segmentation method are solved, and the performance of an unsupervised medical image segmentation algorithm is effectively improved.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA
Color image searching method based on quaternion exponential moment
InactiveCN104484432ASimple designEasy to implementSpecial data processing applicationsColor imageFeature extraction
The invention discloses a color image searching method based on a quaternion exponential moment. The method comprises the following steps: using the quaternion exponential moment for decomposing a color image during a color image searching process; taking a moment value acquired by utilizing the quaternion exponential moment to decompose the color image as an image feature; utilizing a calculation method taking Euclidean distance as the similarity between images to calculate the similarity between different images. The quaternion exponential moment is simultaneously combined with a color feature and a texture feature, so that the color and shape features of the image can be effectively represented. The method has the characteristics of simple design, easiness in implementation and no need of manual marking during an image feature extracting process, so that the complex and easily mistaken manual marking process is avoided and the searching precision and efficiency are greatly increased.
Owner:LIAONING NORMAL UNIVERSITY
Ophthalmic surgery navigation system
ActiveCN111616800AImprove visual recovery after surgeryAvoid Manual LabelingEye surgeryDiagnosticsOphthalmology departmentImaging processing
The invention provides an ophthalmic surgery navigation system. The ophthalmic surgery navigation system provides eye position and rotation information for an intraoperative doctor through integrationwith a surgical microscope, and assists a doctor in performing surgery. According to the system, surgery video is obtained in real time based on an artificial intelligent image processing algorithm,the current frame of image is tracked based on extraction of a plurality of target areas or features, accumulated errors are corrected according to reference images, and finally, information such as eye scaling, displacement, rotation and non-rigid deformation is determined. Eye position information is projected into a surgical microscope, real-time, continuous, automatic and accurate navigation of surgery is achieved, manual marking is avoided, personalized ophthalmic surgery is achieved, surgical quality is improved, and postoperative visual recovery of patients is improved.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA +1
Method and device for generating dress collocation data
PendingCN111767420AAutomatic accumulationPromote rapid accumulationDigital data information retrievalCharacter and pattern recognitionSocial mediaComputer graphics (images)
The invention discloses a method and device for generating dress collocation data, and relates to the technical field of computers. One specific embodiment of the method comprises the following steps:carrying out dress segmentation on each input image to obtain one or more single dress images of each dress collocation image, the input images comprising dress matching images; evaluating the similarity between each single dress image and a dress commodity image in a commodity library so as to select a similar dress commodity image of each single dress image; and matching the similar dress commodity images of the single dress image in each dress collocation image according to a dress collocation principle of the dress collocation image to obtain one or more groups of dress collocation data corresponding to each dress collocation image. The implementation mode can automatically, quickly and accurately accumulate a large amount of dress collocation data with various styles, avoids time andlabor consumption, overcomes personal aesthetic tendency limitation, fully utilizes social media and network resources, and enables the dress collocation data to accord with fashion trends.
Owner:BEIJING WODONG TIANJUN INFORMATION TECH CO LTD +1
Spine MRI image key point detection method based on deep learning
ActiveCN112184617AAvoid the influence of subjective factorsReduce the burden onImage enhancementImage analysisSpine imagingBlock vertebrae
The invention provides a spine MRI image key point detection method based on deep learning. The invention discloses the spine MRI image key point detection method based on deep learning, and the method comprises the steps: firstly detecting and positioning vertebrae in a spine MRI image through a depth target detection network, recognizing S1 (sacral 1) as a positioning spine, filtering a false positive detection result through combining with the structural information of the spine, and judging the fine granularity label of each vertebra; using a key point detection network for detecting six key points including UA, UM, UP, LA, LM and LP of the upper boundary and the lower boundary of each vertebra, determining and correcting the key point positions of all the vertebrae in combination withedge information, and finally developing interactive visual MRI spine image key point automatic labeling software. Spine MRI image key points can be automatically extracted, and the spine MRI image key point extraction method has huge application value in the aspects of medical image analysis, auxiliary medical treatment and the like.
Owner:ZHEJIANG UNIV
Unsupervised multi-document abstract generation method for public opinion analysis
ActiveCN111597327APracticalImprove fluencyNeural architecturesEnergy efficient computingOpinion analysisData mining
The invention discloses an unsupervised multi-document abstract generation method for public opinion analysis. The method comprises the steps: 1, collecting online public opinion news in real time, and automatically dividing news sets according to network hotspots; 2, extracting a single document abstract of each piece of public opinion news in the set in an unsupervised manner; and 3, analyzing all the extracted single-document abstracts in the set to obtain an unsupervised multi-document abstract. According to the method, the problems that an existing multi-document abstract method is relatively low in effect, relatively poor in generative abstract practicability and lack of Chinese public opinion abstract training corpora are solved, so that public opinion news is monitored.
Owner:HARBIN INST OF TECH
Label gumming and pasting device for manufacturing and producing roller type sound boxes
InactiveCN108471590AReasonable structureInnovative designElectrical transducersEngineeringDrive motor
The invention discloses a label gumming and pasting device for manufacturing and producing roller type sound boxes. The device comprises a base, motor seats are installed on two sides of the lower endof the base, a driving motor is connected to the middle of the lower ends of the motor seats, a driving belt pulley is installed at the middle of the front end of the driving motor, a conveying frameis installed at the middle of the upper end of the base, a driven belt pulley is installed at the top end of the conveying frame, a transmission wheel is installed on the rear end of a coaxial position of the driven belt pulley, supporting frames are installed on the two sides of the upper end of the base, a fixing frame is installed at the top end of each supporting frame, a rotating shaft is installed on the right side of the lower end of the fixing frame, a roller is installed at the middle of the rotating shaft, a rolling groove is formed in the outer side of the roller, a rolling ball isarranged in the rolling groove, a lifting rod is connected to the left end of the rolling ball, a lifting shaft is connected to the left end of the lifting rod, and a lifting plate is connected to the lower end of the lifting shaft. By adoption of the label gumming and pasting device disclosed by the invention, automatic gumming and label pasting of sound boxes are achieved, and manual label pasting is avoided, thereby not only improving the label pasting efficiency of the sound boxes, but also reducing the labor intensity of workers, and meeting the manufacture and production demands of large-scale sound box label pasting.
Owner:嵊州市格瑞特电子有限公司
Bidding data named entity recognition method based on pre-training model
ActiveCN113283244AImprove semantic comprehensionAvoid Manual LabelingSemantic analysisCommerceReference modelNamed-entity recognition
The invention relates to a bidding data named entity recognition method based on a pre-training model. The method specifically comprises the following steps: S1, obtaining an open source pre-training model; S2, acquiring an unlabeled corpus, and performing data preprocessing; S3, training the pre-training model in the S1; S4, performing supervised training by using the labeled data to obtain a reference model M; S5, enabling the reference model M to predict the unlabeled data to obtain pseudo-label data; S6, adding the pseudo label data into the training set, adding the real label data into the training set, and jointly training to obtain a model M'; S7, constructing a fragment decoding network; S8, encoding the text input model M'; S9, inputting the text code into a fragment decoding network; and S10, extracting entity fragments and categories thereof. According to the invention, after the model is pre-trained, model decoding is carried out in a fragment identification mode to predict the beginning and ending positions of the entity, the decoding speed can be increased, and an entity result with good precision can be obtained.
Owner:湖南达德曼宁信息技术有限公司
Target detection data set generation method and device, equipment and storage medium
InactiveCN113900989AImprove production efficiencyAvoid Manual LabelingImage enhancementImage analysisComputer hardwareGeneration process
The invention belongs to the technical field of target detection, and discloses a target detection data set generation method and device, equipment and a storage medium. The method comprises the following steps: traversing a preset background image folder path to obtain a traversed current background image; generating a blank annotation file according to a file name corresponding to the current background image; and storing the current background image and the blank annotation file into the initial data set to obtain a target data set. Through the above mode, the data set is generated according to the background image and the blank annotation file, in the case of target detection and identification errors, the background image with the identification errors is stored to the preset background image folder path, and the target data set can be generated through the data set generation process, so that manual annotation is avoided, the data set generation efficiency is high, and thus quickly responding to model optimization work.
Owner:奇酷软件(深圳)有限公司
Multi-feature fusion based color image retrieval method for HSV space image retrieval
InactiveCN105631001AHigh precisionImprove practicalityCharacter and pattern recognitionSpecial data processing applicationsColor imageDecomposition
The invention discloses a multi-feature fusion based color image retrieval method for HSV space image retrieval. According to the method, a color image is transferred from an RGB space to an HSV space in the color image retrieval process, a gray-scale image is decomposed by utilizing non-subsample Shearlet shear waves, color histogram feature extraction and texture index spacing amplitude feature extraction are respectively performed by utilizing different scales of sub-bands obtained through decomposition, finally the similarity of different images is calculated by utilizing an Euclidean distance as an image similarity calculating method, and results are sorted and output according to the similarity from big to small. Compared with single color or texture retrieval, the retrieval accuracy is improved to the greatest degree, and accordingly the problem that the ideal image retrieval efficiency cannot be achieved according to individual color features or individual texture features is solved.
Owner:LIAONING NORMAL UNIVERSITY
Text data relationship extraction method, apparatus and device, and readable storage medium
PendingCN112559770ASolve the problem of lack of training corpusAvoid Manual LabelingRelational databasesNatural language data processingRelationship extractionSentence
The embodiment of the invention discloses a text data relationship extraction method, device and equipment and a readable storage medium. The method comprises the steps of obtaining text data with a keyword tag; constructing sentences according to the keyword tags and a predetermined entity relationship, and taking the sentences and text data as input data of a reading understanding model; and judging whether an answer output by the reading understanding model is a correct entity in the text data or not, and if so, marking the two entities and an entity relationship in the text data. Accordingto the technical scheme, sentences formed by keyword tags and predetermined entity relations and text data serve as input data of a reading understanding model, whether answers of the reading understanding model to the sentences are correct entities in the text data or not is judged, and if yes, the entities in the text data and the entity relations are marked; the problem of lack of training corpora in the application field of relation extraction is solved, and the cost is reduced.
Owner:BEIJING UNIV OF POSTS & TELECOMM
Automatic test tube label pasting device
ActiveCN109319245AGuaranteed speedQuality assuranceLabelling machinesMedical deviceSignal processing
The invention discloses an automatic test tube label pasting device and belongs to the field of medical devices. The device comprises a bottom plate, a storage unit, an isolation unit, a clamping wheel, a label separating unit, a signal processing unit and a plurality of induction units. The isolation unit is used for separating single test tubes. The clamping wheel is used for moving the test tubes so as to perform label pasting. According to the automatic test tube label pasting device, the test tubes are separated from one another after being stored through the isolation unit, the labels are separated from label paper by means of the label separating unit, then the clamping wheel is used for driving the test tubes to run and to be pasted with the labels, the labels are pressed tightly by means of elastic assemblies, the test tube labels are further pasted automatically, in addition, the structure is compact, the device is fast and efficient to use, simplex manual label pasting is avoided, and the label pasting speed and quality are guaranteed. Furthermore, the signal processing unit and a plurality of sensors are arranged, and the applicability of the automatic test tube label pasting device is guaranteed to a greater extent.
Owner:NANFANG HOSPITAL OF SOUTHERN MEDICAL UNIV
Cloud platform abnormal log analysis method
PendingCN112685215AFault warningImprove stabilityFault responseCharacter and pattern recognitionEngineeringData mining
The invention discloses a cloud platform abnormal log analysis method. The method comprises the following steps of S1, collecting historical operation logs of a cloud platform and performing preprocessing; s2, converting the obtained historical log content into digital vector representation; s3, clustering division is carried out on the logs represented by the digital vectors; s4, constructing a deep neural network to learn the encoded log; and S5, analyzing the newly generated log by using the trained deep neural network to obtain alarm information, tracing the alarm information, and judging a fault point. According to the invention, the historical logs are learned by constructing the deep neural network, and then the trained deep neural network is applied to the analysis of the existing logs, so that the possible faults in the cloud platform operation process can be pre-warned by analyzing the generated log content. The abnormity in cloud parallel operation can be positioned and solved in advance, and the operation stability of the cloud platform is improved.
Owner:SHANDONG LANGCHAO YUNTOU INFORMATION TECH CO LTD
Paper job page number identification method based on Fast-RCNN
ActiveCN110532938AAvoid the problem of low recognition accuracyImprove robustnessCharacter recognitionGraphicsData source
The invention belongs to the technical field of image recognition in particular to a paper job page number recognition method based on a Faster-RCNN, and aims to solve the problems that in the prior art, a training set is not rich, and a page number training set of a graph and / or image combination style does not exist, so that the page number recognition accuracy is low, and some page numbers cannot be recognized. The method comprises the following steps: calculating a page number center coordinate in a page picture through a paper job page number positioning method, and obtaining the page number picture by using a rectangular frame; and obtaining a corresponding page number category through the page number identification model. The page number identification model is constructed based ona Faster-RCNN network, and the training sample set, the sample label and the to-be-identified page number picture are selected from the same book. The page numbers of the same book are used as the data source, sample expansion is carried out, the sample sets with different effects are generated for the page numbers of different styles, the labels corresponding to the samples are automatically generated, the page number recognition accuracy is high, the robustness is high, and the efficiency is high.
Owner:BEIJING YUNJIANG TECH CO LTD
Unsupervised human face intelligent accurate recognition method and system
ActiveCN108875455AGuaranteed accuracyProcessing speedCharacter and pattern recognitionFeature vectorCluster algorithm
The invention discloses an unsupervised human face intelligent accurate recognition method and system. The method comprises the steps of preliminarily classifying extracted human face picture eigenvectors by adopting a density clustering algorithm, and performing model parameter learning on a training set by adopting a logistic regression algorithm, thereby obtaining initialized logic regression parameters; performing logical regression prediction processing on the human face picture eigenvectors in the test set according to the initialized logic regression parameters, and performing probability normalization calculation on obtained predicted values to obtain corresponding probability values; and when the probability values are greater than a preset confidence rate threshold value, allocating the human face picture eigenvectors currently subjected to the logical regression prediction processing to corresponding tags, and forming a new training set. According to the method, the accuracyof human face picture recognition is ensured while the clustering capability of the system is enhanced; and the method is based on an unsupervised classification algorithm, so that the manual taggingis avoided, the manpower and material resources are saved, and the processing speed of human face picture recognition is increased.
Owner:TCL CORPORATION
Unsupervised image classification method based on automatic encoder
InactiveCN113269282ASimple structureAvoid Manual LabelingCharacter and pattern recognitionNeural architecturesBackground informationAutoencoder
The invention discloses an unsupervised image classification method based on an automatic encoder. The method comprises the following steps: S1, designing an automatic encoder model based on a convolutional neural network architecture; S2, enabling an auto-encoder model to extract feature information in the image through multi-task loss; S3, preparing to-be-classified image data, and carrying out the self-encoder model training; S4, after the auto-encoder model is trained, enabling the auto-encoder model to complete the encoding of feature information in the image; S5, filtering the noise and background information in the original image through coding of the auto-encoder model, and completing the image classification. According to the method, learning can be carried out without any label or model, so that the image classification task is completed, and the labor cost is reduced.
Owner:LYNCWELL INNOVATION INTELLIGENT SYST ZHEJIANG CO LTD
Label and method for manufacturing same
ActiveCN105118379ASolve the problem of overflow glueAvoid Manual LabelingStampsLaminationPulp and paper industryCoating
The invention provides a label and a method for manufacturing the same. The method includes: a step of coating and combining in which a surface material, glue, and bottom paper are combined to form a first label material which has a plurality of to-be-cut second label materials in a length direction, and the glue is applied locally so that a glued area of each second label material is provided with unglued areas on two sides of the glued area; a step of cutting in which the first label material is cut into a plurality of second label materials and the two ends of each second label material are provided with an unglued area each; a step of glue removal and printing in which the glued surface material and the bottom paper of each second label material are separated, then glue cured frames are formed through printing at the glued areas, and then the bottom paper is combined to the surface materials, and third label materials are formed by printing on the surfaces of the surface materials; a step of die cutting and waste discharging in which die cutting and waste discharging are conducted on the third label materials so as to form finished labels with the glue cured frames. According to the invention, the method of local glue coating and local glue removing addresses the problem in label materials of glue spill in the processes of printing, die cutting, printing, and automatic labeling.
Owner:上海印标包装有限公司
Hole marking method and device, computer equipment and readable storage medium
PendingCN113935091AImprove drawing efficiencyReduce labor costsGeometric CADDesign optimisation/simulationComputer deviceMechanical engineering
The invention relates to a hole marking method and device, computer equipment and a readable storage medium. The method comprises the steps of obtaining a first parameter of a wall body and a second parameter of a hole in a two-dimensional wall body drawing through a Revit platform, obtaining a three-dimensional contour model of the wall body according to the first parameter, editing the three-dimensional contour model to obtain a three-dimensional wall body model, and based on the second parameter, carrying out information labeling on the hole in the three-dimensional wall body model. By adopting the method, the three-dimensional wall body model can be constructed through the first parameter of the wall body in the two-dimensional wall body drawing, the wall body model does not need to be manually drawn, the drawing efficiency of the three-dimensional wall body drawing is improved, information labeling is automatically performed on the hole in the three-dimensional wall body model through the second parameter of the hole, manual labeling can be avoided, the labor cost is saved, and the hole marking efficiency is improved.
Owner:GUANGZHOU POWER SUPPLY BUREAU GUANGDONG POWER GRID CO LTD
Automatic detection method for minimum repetition unit of printed fabric image
ActiveCN109165650AAvoid Manual LabelingEasy to handleCharacter and pattern recognitionPattern recognitionWorkload
An automatic detection method for a minimum repetition unit of a printed fabric image includes scanning printing fabric into an image; manually selecting a rectangular area containing a plurality of pixels in the image, and selecting pixels of at least two vertices as key points; detecting a rectangular sub-image similar to the rectangular area image in the image, marking key points of the rectangular sub-image, adjusting pixel distances to minimize the number of key points, namely similarity points; identifying the minimum repeat units based on the number of similar points. The method can realize the detection of the minimum repetition unit for processing the color printed fabric and the complex printed fabric with various patterns, and greatly reduces the difficulty and workload of colorseparation and plate making.
Owner:JIANGSU OCEAN UNIV
Method and system for normalization of colloquial symptoms
InactiveCN109543179AImprove standardizationAvoid Manual LabelingMetadata text retrievalSemantic analysisCosine similarityMedical record
A method for normalizing colloquial symptoms includes: receiving a colloquial symptom input by a user; Mapping the colloquial symptom to a pre-stored set of standard symptoms, and obtaining a standardsymptom having the highest cosine similarity score with a word vector of the colloquial symptom in the standard symptom set, and setting the standard symptom having the highest score as a normalizedsymptom of the colloquial symptom. The colloquial symptoms entered by the user are mapped to the preserved standard symptom set, and the standard symptom with the highest cosine score of the word vector of the colloquial symptoms is directly regarded as the normalized symptom of the colloquial symptoms. The invention avoids that the information input by the user can not be processed through the intelligent terminal. At that same time, a large amount of manpower time is avoid to be consumed for manual label. Normalization of symptoms into standard forms will greatly facilitate the standardization of medical records, medical atlas-based reasoning, electronic information exchange, and other applications.
Owner:北京左医科技有限公司
Medical inspection sample Internet of things intelligent management and control information system
ActiveCN108922581BImprove accuracyEasy to useTransmissionLaboratory analysis dataEngineeringIntelligent management
Owner:CHONGQING MICRO IDENTIFICATION TECH
Deep learning-based pathology image automatic segmentation system
PendingCN113409293AImprove segmentation efficiencyHigh precisionImage enhancementImage analysisAutomatic segmentationCluster algorithm
The invention relates to the technical field of image processing, in particular to a Deep learning-based pathology image automatic segmentation system, and the system comprises: an image collection module which is used for collecting a plurality of pathological images; the image segmentation module that is used for uniformly dividing the plurality of pathological images into a plurality of segmented images; the image labeling module used for dividing the segmented image into a plurality of regions according to a preset clustering algorithm, and labeling each region with a label in each region to obtain a plurality of label images; the model training module used for taking the segmented image and the label image as input and taking the corresponding real segmented image as output, and training to obtain a deep learning segmentation network model; and the prediction module used for inputting the segmented image to be segmented and the label image into the deep learning segmentation network model to obtain a predicted segmented image, wherein the predicted segmented image is used as a reference basis for doctors. According to the invention, unsupervised pathological image segmentation is realized, the image segmentation precision is improved, and the segmentation error is reduced.
Owner:SHANGHAI FIRST PEOPLES HOSPITAL
Visual navigation guide point marking method and device and computer equipment
ActiveCN111813131AAvoid manual labelingImprove efficiencyCharacter and pattern recognitionPosition/course control in two dimensionsComputer visionFeature matching
The invention relates to a visual navigation guide point marking method and device, computer equipment and a storage medium. The method comprises the following steps of: acquiring sequential image information acquired from the environment when an unmanned vehicle runs, and determining a first target point in a first image according to a preset rule, performing calculation through image feature matching and affine coordinate transformation to obtain a second target point, projected to a second image, of the target point of the first image, using the second target point as a guide point of the second image, and acquiring a control strategy when no person performs autonomous navigation in the scene according to the guide point. By adopting the method, the guide points corresponding to a series of images can be automatically generated, manual marking is avoided, and the method has the advantages of high efficiency and good consistency.
Owner:NAT UNIV OF DEFENSE TECH
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