80results about How to "Automated Extraction" patented technology

Embodiments of the present invention are directed to quantitative analysis of tissues enabling the measurement of objects and parameters of objects found in images of tissues including perimeter, area, and other metrics of such objects. Measurement results may be input into a relational database where they can be statistically analyzed and compared across studies. The measurement results may be used to create a pathological tissue map of a tissue image, to allow a pathologist to determine a pathological condition of the imaged tissue more quickly.

Embodiments of the present invention are directed to quantitative analysis of tissues enabling the measurement of objects and parameters of objects found in images of tissues including perimeter, area, and other metrics of such objects. Measurement results may be input into a relational database where they can be statistically analyzed and compared across studies. The measurement results may be used to create a pathological tissue map of a tissue image, to allow a pathologist to determine a pathological condition of the imaged tissue more quickly.

Embodiments of the present invention are directed to quantitative analysis of tissues enabling the measurement of objects and parameters of objects found in images of tissues including perimeter, area, and other metrics of such objects. Measurement results may be input into a relational database where they can be statistically analyzed and compared across studies. The measurement results may be used to create a pathological tissue map of a tissue image, to allow a pathologist to determine a pathological condition of the imaged tissue more quickly.

The invention discloses a concept relation label drawing method based on a semantic co-occurrence model. The concept relation label drawing method includes obtaining co-occurrence context phrase of a concept relation pair through inverted searching with offset in a relation label drawing process based on the semantic co-occurrence model; obtaining a candidate relation label by combining shallow parsing and weighting word window filtering; and choosing a cluster label largest in weight after semantic relativity cluster is performed to serve as a concept relation label. By means of the concept relation label drawing method based on the semantic co-occurrence model, accuracy rate and recalling rate of concept relation drawing are improved, automatic drawing of few and scattered semantic relation concept relation labels among large number of concepts is achieved, and quality of concept label drawing is improved.

The invention discloses a city edge region extraction method based on multi-source data fusion, and the method comprises the steps: selecting a plurality of pieces of city edge feature data as data sources, and respectively determining a city edge region recognition index factor of each piece of city edge feature data; after data standardization processing is carried out on the urban edge area identification index factors, calculating index values and index weights of the urban edge area identification index factors, and obtaining urbanization characteristic values through calculation of the index values and the index weights; performing urban edge area mutation point identification and extraction according to the urbanization feature value to obtain an urban edge area mutation point cluster; performing spatial position and attribute feature clustering on urban edge area mutation point clusters, performing inner and outer boundary extraction on each clustering cluster, and obtaining urban edge area boundaries. By the adoption of the city edge area extraction method based on multi-source data fusion, automatic extraction of the boundary of the city edge area is achieved, and the boundary recognition precision of the edge area is improved.

The invention relates to the technical field of remote sensing technologies, in particular relates to a landslide deformation monitoring method and a visual service platform, provides a landslide monitoring system method based on optical and radar data fusion by starting from landslide area features and utilizing the advantages brought by optical and radar image fusion, and solves the problems that a traditional landslide deformation monitoring method is low in precision, large in workload and high in cost. A landslide identification module, a deformation processing module, a risk assessment early warning module, a data management module and a visualization module are included. The landslide identification module is used for identifying a landslide area in a remote sensing image; the deformation processing module is used for extracting deformation characteristics in the landslide area; the risk assessment and early warning module is used for performing assessment and early warning on the risk of each landslide disaster; the data management module is used for storing various data in the system; and the visual analysis module is used for landslide area deformation data analysis and visual display.

The invention provides a graph-model consistency examination method and system based on a knowledge graph, and the method comprises the steps: building a drawing body according to the structural information of a drawing; establishing a model ontology from a BIM model file; carrying out semantic fusion on the drawing ontology and the model ontology to form a graph-model fusion knowledge graph; and extracting related review points from the graph-model fusion knowledge graph, and completing consistency review. Meanwhile, the invention provides a corresponding terminal and a computer storage medium. According to the method, the overall conception that information is extracted from the building model and the design drawing file to form the knowledge graph and then consistency review is conducted is adopted, labeling information in the design drawing can be accurately extracted, attribute information of all components is included, and the labeling information is accurately compared with information in the building model; in the examination result, an examination result can be given according to the component type.

The invention provides an efficient extraction device which comprises a tank body, wherein the tank body is provided with a feed port, a discharge port, a liquid inlet, a liquid outlet, an air inlet and an air outlet, and a cavity is arranged in the tank body. The efficient extraction device is characterized in that a filter screen dividing the cavity of the tank body into a soaking extraction chamber and a liquid storage chamber is arranged in the tank body; and helical blades are arranged along the chamber wall of the soaking extraction chamber. The material and extraction solvent entering the soaking extraction chamber of the tank body can be subjected to continuous stirring and sufficient contact in the pushing process, the extraction efficiency is high, and the extract is not polluted; meanwhile, the circulation or heating of the extract can be flexibly controlled as necessary during the extraction process so as to obtain more complete active ingredients; and the filtering separation is synchronously completed in the extraction process, the extraction time and subsequent condensation time are greatly shortened, the energy consumption is reduced, the pollution discharge is avoided, the occupied area is small, the filter screen is replaceable, the efficient extraction device is protected from blockage, is safe and reliable, can be enlarged and is favorable for realizing automatic extraction.

The invention discloses an automatic processing method, apparatus and device for web interface elements, and a medium, and relates to the technical field of financial. The automatic processing methodfor the web interface elements comprises the following steps: when a web interface detects an input completion instruction of a URL address, obtaining a full page corresponding to the URL address; analyzing the htlm text in the full page through a third-party tool of preset communication, and traversing all page elements corresponding to the htlm text so as to screen target elements from all the page elements according to preset configuration information; and automatically naming, positioning, storing and processing the target element. The automatic processing method for the web interface elements solves the technical problem that in the prior art, web interface elements are processed in a recording and playback mode, and manpower and material resources are consumed too much.

The invention discloses a nucleic acid detector which comprises a base, a chip mounting assembly, a heating device, an optical detection device and a mechanical arm assembly; the chip mounting assembly is arranged on the left side part of the base and comprises a box body, a chip groove for accommodating a micro-fluidic chip is formed in the box body, and the chip groove is provided with a groove opening facing upwards; the heating device is arranged on the front side or the rear side of the chip mounting assembly; the optical detection device is arranged below the chip mounting assembly and is provided with an emitted light emitting part and an exciting light receiving part which are used for facing the lower end part of the micro-fluidic chip; the lower end part of the box body is provided with a hollow part capable of allowing emitted light to enter the chip groove and allowing exciting light to be emitted out of the chip groove; and the mechanical arm assembly comprises a mechanical arm capable of moving in the left-right direction, the mechanical arm is provided with a fork-shaped piece, and the fork-shaped piece is provided with a joint groove allowing the end of a piston of the micro-fluidic chip to be clamped in. The nucleic acid detector is compact in structure and small in size.

The invention relates to a state diagram-based coding verification method. The method comprises the following steps: 1) describing a target software requirement by using an ArgoUML state diagram, and carrying out requirement analysis; 2) taking a file output by ArgoUML as an extraction object to extract a state diagram description file; 3) analyzing the state diagram description file so as to obtain a node state, migration information and a state attribute of the state diagram; 4) converting the ArgoUML state diagram into a target MuSMV code according to the obtained node state, migration information and state attribute of the state diagram; 5) automatically extracting an inspection property and providing the inspection property to users in an interaction manner for secondary edition; and 6) calling an NuSMV inspector to execute inspection, returning whether the inspection property is satisfied or not, and if the inspection property is not satisfied, giving an error position point and displaying a route sequence. Compared with the prior art, the method disclosed in the invention can be used for carrying out modeling aiming at the software requirement and realizing automatic inspection, and enabling the design analysts to not consider how to compile complicated NuSMV programs any more, wherein the conversion is realized automatically.

The embodiment of the invention provides an electronic medical record structured method and system and related equipment, which are used for improving medical record information extraction efficiency.The method comprises the steps: obtaining a target electronic medical record text, and performing word segmentation on the target electronic medical record text according to a preset corpus library and a preset word segmentation rule to form a word segmentation set; matching preset keywords with segmented words in the segmented word set, and determining a data element corresponding to a successfully matched target keyword as a target type data element, each keyword at least corresponding to one type of data element; extracting a data element value of the target type data element from the target electronic medical record text according to an extraction rule of the target type data element; and associatively storing all target type data elements of the target electronic medical record text.

The invention discloses a method for quickly establishing an intelligent traffic three-dimensional field. The method comprises the following steps: step 1, establishing a static model which comprises a road model, a building model, a plant model and a terrain model; step 2, establishing a dynamic model; step 3, performing state control, decision analysis and vehicle tracking according to the static model and the dynamic model. According to the method for quickly establishing the intelligent traffic three-dimension field, a three-dimensional scene is quickly established; besides, dynamic factors are introduced into the road traffic environment, so that the vividness of the virtual traffic environment is improved, and the real state of the road traffic environment is effectively and vividly reproduced.

The embodiment of the invention provides a webpage information extraction method and device. The webpage information extraction method comprises the steps of determining candidate elements and text information of a webpage according to a DOM tree of the webpage; determining candidate position information of the webpage according to the display page screenshot of the webpage; determining a first probability that each candidate element serves as a target extraction element and a second probability that each candidate position serves as a target extraction position according to the candidate position information and the text information of each candidate element; determining a target extraction element and a target extraction position from each candidate element and each candidate position according to the first probability and the second probability; and performing information extraction on the webpage according to the candidate elements determined to be the target extraction elements and the candidate positions determined to be the target extraction positions. The text information and the candidate position information of the candidate elements of the webpage are extracted, and theneural network model and the spatial probability distribution model are used for positioning the extraction position, so that the positioning precision and the fault-tolerant rate of webpage information extraction are improved, and automatic extraction of webpage information is realized.

The invention provides a method and a device for calculating data processing based on VASP software, which relates to the technical field of data processing. The VASP file is extracted and stored in the target data table, then the VASP file is imported into the template according to the extracted VASP file, the VASP file is imported into the data processing system according to the imported template, and finally the VASP file is processed to generate the data record. The VASP software-based computing data processing method and device provided by the invention have the advantages of simpler processing mode and faster processing speed.

The invention discloses an automatic extraction method and apparatus for feature points of three-dimensional tooth grid models, which relates to the technical field of oral cavity, and can solve the problem of low efficiency of manually extracting the feature points of the three-dimensional tooth grid models in the prior art. The method comprises the steps of determining coordinates, in the corresponding three-dimensional tooth grid models, of the feature points in a training set; performing statistics on the coordinates of the same feature points of the same teeth, thereby determining position ranges of the feature points in the target three-dimensional tooth grid model; by utilizing the first model, determining the specific positions of the feature points in the target three-dimensionaltooth grid model from the position ranges; and when at least two specific positions of one feature point determined by utilizing the first model exist, determining the unique position of the one feature point from the at least two specific positions. The automatic extraction method and apparatus is mainly suitable for a scene of automatically extracting the feature points for the three-dimensionaltooth grid models.

The invention provides a bill element extraction method and device, electronic equipment and a readable storage medium, and is applied to the technical field of image processing, and the method comprises the steps: carrying out the image recognition of a bill image to determine a to-be-recognized text region, and carrying out the classification of the text information of the to-be-recognized textregion through a natural language understanding technology, and determining the type of the target bill, and then extracting element information of the target bill from the text information corresponding to the to-be-identified area based on the type of the target bill. Therefore, the automatic extraction of the bill element information is achieved, and the bill element extraction efficiency is improved.

The invention discloses an indoor positioning environment feature point extraction method, and the method comprises the steps: obtaining the two-dimensional LiDAR point cloud data of an indoor space through a two-dimensional LiDAR collection device and obtaining the RSSI (Received Signal Strength Indicator) of signals of opportunity of a wireless communication device disposed indoors through an intelligent terminal; acquiring indoor environment characteristics when the RSSI is acquired from the two-dimensional LiDAR point cloud data, extracting indoor space structure characteristics with highpotential in combination with a collector track, further calibrating a signals of opportunity RSSI sequence peak value, and constructing indoor positioning environment characteristic points. Comparedwith a traditional method, the method has the advantages that the requirement on an indoor map is avoided when the indoor positioning environment feature points are extracted, the indoor space environment with high potential is obtained by utilizing the two-dimensional LiDAR point cloud and the collector track data, the feature points are automatically extracted, and the indoor positioning and navigation are enhanced. The method is suitable for the technical field of indoor positioning.

The invention relates to the technical field of artificial intelligence and data processing. The invention provides a video analysis method and a device based on artificial intelligence and a medium.According to the method, an original video can be split to obtain video segments; the dining condition of each table is judged in a targeted manner; feature extraction on each video segment is carriedout by utilizing the model; automatic feature extraction is realized by combining an artificial intelligence means; analysis of features is carried out, analysis data is obtained, connection with a specified sensor is adopted, calling of target data of each video segment collected by the specified sensor is carried out, and calculation is carried out according to the analysis data and the targetdata to obtain a video analysis result, so that comprehensive and targeted analysis can be performed on a video based on an artificial intelligence means, and the analysis efficiency is higher. The invention also relates to the blockchain technology. A plurality of pre-trained models are stored in the blockchain.

The invention provides a surface deformation information extraction method based on point cloud data. In order to overcome the defects of an existing method for extracting deformation information based on point cloud data, deformation information between surfaces is extracted through curved surface matching operation, the characteristic of high spatial resolution of the point cloud is fully utilized, the extracted deformation information not only comprises three-dimensional displacement deformation, but also comprises torsional deformation of the surfaces, and a new thought and technical reference are provided for extracting the deformation information based on point cloud data.

The invention discloses a mobile application APK (Android Package) file embedded privacy policy extraction method and belongs to the field of Android mobile terminal application software analysis and detection. The method specifically comprises the following steps of firstly, selecting a to-be-detected APK file for decompiling and rule matching, obtaining all URL (Uniform Resource Locator) links, respectively crawling each webpage content, and extracting feature words in a privacy policy text; meanwhile, collecting feature words of a plurality of webpages to train a dichotomy model in advance; inputting feature words of the to-be-detected APK file into the trained dichotomy model one by one, judging whether a privacy policy page exists in an output result or not, and if yes, outputting a privacy policy and ending; otherwise, performing automatic dynamic testing, monitoring request addresses in the traffic, extracting corresponding URL links, crawling contents of pages to extract feature words, inputting the feature words into a dichotomy model for judgment, and ending till a privacy policy page is found or a set traversal depth is exceeded. According to the method, dynamic and static tests are combined, so extraction efficiency and the success rate of privacy policies are improved.

The invention relates to an information extracting method for a remote sensing image continuous target field based on cluster analysis, and belongs to the technical field of information extraction. The method comprises the following steps: carrying out feature analysis on original image data to find a maximum reference value or a minimum reference value of area character data of the target field to be extracted; carrying out threshold segmentation on the image data according to the maximum reference value or the minimum reference value; carrying out cluster analysis on the image data subjected to the threshold segmentation; rejecting a false target field from a target continuous field obtained by the cluster analysis; and carrying out mask processing on the image subjected to the false target field rejection and an original image to obtain a result image subjected to information extraction. With the technical scheme, the continuous field target can be identified and extracted more automatically; by using the cluster mode, on the basis of a target object, the image features endowed by the continuous field targets in different images are fully considered and the target which is really needed to be identified can be identified and extracted, therefore, compared with the prior art, the information extracting method has higher accuracy.

The invention discloses an aircraft surface leading edge attachment line area extraction method, and relates to the technical field of aerodynamic thermal engineering. According to the technical scheme, based on aircraft geometric appearance characteristics and a surface non-viscous flow field, the attachment flow area of the leading edge of the aircraft is jointly judged by combining a Jacobian matrix discriminant of the surface linear vector field and the discrete curvature of the geometric shape, wherein the extracted attachment line areas are continuously distributed at the characteristic leading edge of the aircraft. According to the invention, the continuously distributed characteristic leading edge attachment line flow area can be rapidly and automatically extracted, the change of the position of the attachment line area can be captured when the flight working condition changes, and the capture applicability to the attachment line areas of different types of aircrafts is good; the invention is used for aerodynamic thermal environment engineering calculation, the aircraft characteristic leading edge sweepback cylinder heat flow calculation formula of the attachment line area can be conveniently determined, and the accuracy of characteristic leading edge aerodynamic thermal environment calculation by the engineering method is improved.

The invention discloses a method and device for automatically extracting a background noise frequency dispersion curve, and the method comprises: obtaining background noise data recorded by a seismic station, carrying out the preprocessing, cross-correlation and superposition of the background noise data, obtaining an empirical green function, carrying out the vector wave number domain transformation of the empirical green function, and obtaining a frequency dispersion spectrum; according to the frequency dispersion spectrum and a Res-Unet++ network model, obtaining a candidate frequency dispersion area; and according to a gradient method and a chasing method, extracting and classifying frequency dispersion points of the candidate frequency dispersion area, and obtaining a target frequency dispersion curve. According to the embodiment of the invention, the automatic extraction of the frequency dispersion curve can be realized, the high-order frequency dispersion curve which is poorer in extraction by the extreme value method can be extracted, a lot of time of researchers is saved, and the working efficiency of the researchers is improved.

The invention provides a text error correction method and a model training method and device thereof, and relates to the technical field of character recognition, and the model training method comprises the steps: obtaining a sample text containing keywords according to the preset keywords; formatting the sample text; inputting the sample text subjected to formatting operation into a preset initial neural network model for training; and when an output result in the preset initial neural network model meets a preset expected threshold, obtaining a model for text keyword extraction. A text to berecognized is input into a text keyword extraction model which is trained in advance, a text keyword extraction result is output, and the text keyword extraction result is compared with a preset standard file for error correction. The text keyword extraction model is obtained by training the neural network model, so that automatic extraction and automatic correction of the text keywords are realized, the manual operation process is reduced, and reduction of writing errors in the text is facilitated.

The embodiment of the invention provides a Sea ice extraction method and device based on superpixel segmentation, and equipment. The method comprises the following steps: carrying out superpixel segmentation on a non-land part of an original remote sensing image by adopting an SLIC superpixel segmentation algorithm; according to the super-pixel segmentation result, based on the gray level co-occurrence matrix, calculating the mean value of the contrast and entropy of each super-pixel, and generating a feature image based on the super-pixels; and calculating a contrast threshold and an entropythreshold by adopting an Otsu threshold detection method, classifying the seawater area and the sea ice area, and extracting the sea ice area. In this way, automatic extraction of the sea ice can be achieved, a reference basis is provided for marine activity extraction in the industries of marine shipping, marine oil exploitation and the like, the sea ice serves as an important participant of global climate change, and sea ice extraction further provides technical support for climate change research.

A method for automatically extracting a working face area image of constructional engineering comprises the steps of obtaining N building site photos to form a photo group, conducting aerial triangulation analysis on the photo group to obtain pose information of the photos, then reconstructing a scene three-dimensional model, and obtaining a projection matrix P<(i)> based on the pose information of the photos and a calibration matrix K<(i)> of the photos; according to the point cloud and project design information of the scene three-dimensional model, obtaining the positions of M working face areas, and obtaining a face domain Omega<(j)> corresponding to the M working face areas; in the N photos, projecting the Omega<(j)> through the projection matrix P<(i)> to obtain a projection area omega (ij) on the ith photo, and finding out the projection omega<(j)>max with the highest Omega<(j)> resolution from the projection areas of the N photos, and converting omega<(j)>max into a working face area orthographic image omega(-)<(j)>max by using the homography matrix H<(ij)>C[Omega] of the image under the Omega<(j)> local coordinate system derived fromomega<(j)>max by the invention. The extraction method can automatically extract a working face area image from a single photo with exact physical significance and high fidelity.

The invention discloses a Pakistani land cover information extraction method based on multi-source spatial data. The method mainly comprises the following two steps of: 1, multi-source spatial data collection and processing: firstly, collecting multi-source spatial data such as optics, SAR (Synthetic Aperture Radar), light and digital elevation covering the Pakistani state, secondly, carrying outrelevant processing such as seasonal synthesis and geographic reference unification, and finally, superposing and merging the multi-source spatial data into a comprehensive data set; and 2, land coverinformation extraction and mapping: firstly formulating a Pakistani land cover classification system, secondly collecting training data and test data, constructing a land cover classifier again, andfinally automatically extracting the land cover information. According to the method provided by the invention, respective advantages of various spatial data can be well and comprehensively utilized to realize automatic extraction of the Pakistani land cover information, and the method has very high operability and practicability.

The invention discloses a voice personality prediction method based on the convolutional neural network, comprising the following steps: S1, establishing a training sample set, including: converting voice data files into a spectrogram, performing big five personality questionnaire tests on acquisition subjects, calculating average value and standard deviation of personality dimension scores, and marking the personality dimension scores which meet the preset requirements; S2, training a convolutional neural network model, including: training the neural network model by the BP algorithm, calculating network errors and updating weights during iteration, training until accuracy of a validation is no longer increased and then stopping training, and saving neural network parameters as the neuralnetwork model; and S3, performing personality prediction on voice data to be tested by the utilization of the convolutional neural network model. Through the technical scheme, the disadvantage that atraditional method requires strong prior knowledge to assist extraction of features with distinguishing degree is overcome, and automatic extraction of phonetic features is realized.

The invention provides a high-resolution image rape extraction method based on a deep learning algorithm, the model fuses DRN and an improved U-Net semantic segmentation model, comprises two core modules of Encoder and Decoder, and realizes autonomous learning of spatial features and spectral features of a high-resolution No.2 image and automatic extraction of a rape pixel level. According to the model, a Gaofen-2 image in the flowering period (from the end of February to the middle of April) of oilseed rape is taken as a data source, training and testing are performed through marked oilseed rape samples, the oilseed rape samples are increased through a data enhancement algorithm, and an optimized oilseed rape extraction model is obtained by adjusting model parameters. When the model is applied, a data input cutting strategy and a result output cutting strategy are provided to realize rape extraction of input images of any size. Compared with a traditional classification analysis method based on pixel and statistical theory and an object-oriented classification algorithm, the method makes full use of the spatial and spectral features of the Gaofen-2 image, realizes autonomous learning of semantic features for rape extraction, and improves the precision of rape extraction and the model generalization ability.