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76 results about "Feature synthesis" patented technology
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Modeling method of characteristics of population space-time dynamic moving based on multisource data fusion
InactiveCN101694706ABig amount of dataQuality improvementData processing applicationsDetection of traffic movementSimulationCharacteristic space
The invention provides a modeling method of the characteristics of population space-time dynamic moving based on multisource data fusion. The modeling method comprises: A. inputting map data, mobile phone locating data and floating vehicle data into a system and managing data organization according to requirements; B. establishing a spatial analysis model of the characteristics of population moving based on the mobile phone locating data and the floating vehicle data; C. applying the spatial analysis model of the characteristics of the population moving to carry out multisource data fusion of the map data, the mobile phone locating data and the floating vehicle data to obtain integrated information of the characteristics of the population moving; and D. analyzing the characteristics of various population moving according to the integrated information of the characteristics of the population moving and publishing an analyzed result by the geographic information system. The modeling method can acquire data of urban population space-time dynamic distribution and moving characteristics with large data amount, high quality and space-time characteristics, obtain basis of accurate population distribution and population moving characteristics, and provide decision-making supports for urban planning, land use planning, transportation planning and the like.
Owner:SHENZHEN INST OF ADVANCED TECH
Multi-characteristic synthetic recognition method for outdoor early fire disaster
InactiveCN101315667AAvoid interferenceReduce false negative rateCharacter and pattern recognitionFire alarm radiation actuationImaging processingShape change
The invention relates to a method for the comprehensive recognition of various features of outdoor incipient fire, pertaining to the technical field of fire monitoring and image processing. The method comprises the steps that: 1. an infrared image is obtained by a thermal imaging instrument; 2. grey scale processing, threshold segmentation and filtration processing are carried out to the fire infrared image; 3.further analysis is carried out to a suspected fire flame image to obtain the following five criterions: (1) the flame image color distribution criterion; (2) the flame image change rate criterion; (3) the flame image area extending and increasing criterion; (4) the flame image circularity criterion; (5) the flame image shape changing criterion; 4. judgment is comprehensively carried out by utilizing a neural network and taking the criterions of 1 to 5 as input so as to obtain the final result that whether the fire occurs. The method overcomes interference to aspects such as natural lights, etc. in the fire recognition process, and reduces the rate of missing report and the rate of false report of the fire.
Owner:NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
Method for optimizing tight oil horizontal well crack network parameters through transformation volume
The invention discloses a method for optimizing tight oil horizontal well crack network parameters through the transformation volume, and belongs to the field of tight oil horizontal well reservoirs. According to the method, according to a tight reservoir, firstly, the geologic feature of the reservoir is evaluated, the specific reservoir condition for volume fracture to form a volume crack network system is explicated, then, the influences of different transformation volumes and crack arrangement modes of horizontal well volume fracture on capacity are studied, and the specific crack network parameters are optimized. The method at least includes the steps that firstly, a basic crack network feature comprehensive evaluation method for tight reservoir volume fracture is established; secondly, a capacity prediction and simulation model method for tight oil volume fracture is established. The tight oil layer horizontal well fracture crack network parameters are optimized through the transformation volume formed in the fracture process, the transformation volume is formed in a tight oil layer, a matrix seeps towards a crack at the shortest distance, the driving pressure of effective flow is greatly reduced, and flow under the extremely-low permeability condition is achieved; the single well capacity can be greatly improved.
Owner:PETROCHINA CO LTD
Digital ink database searching using handwriting feature synthesis
InactiveUS20050222848A1Still image data retrievalDigital data processing detailsFeature vectorHandwriting
A system and method for ink database searching using handwriting feature synthesis is disclosed which allows a digital ink database to be searched using a text-based query. Using a writer-specific handwriting model derived from a handwriting recognition system or suitable training procedure, a text query is converted into feature vectors that are similar to the feature vectors that would have been extracted had the author of the digital ink database written the text query by hand. The feature vectors are then used to search the database. This allows the searching of a digital ink database when the only input mechanism available is text entry, and can allow a person other than the author of the digital ink database to search the digital ink database.
Owner:SILVERBROOK RES PTY LTD
Method for identifying overhead high-voltage wire automatically from infrared image
InactiveCN102930280AUniform brightness valueImprove reliabilityCharacter and pattern recognitionPicture interpretationHigh tension lineImage segmentation
The invention provides a method for identifying an overhead high-voltage wire automatically from an infrared image, and aims to provide a method for extracting an overhead high-voltage wire from an infrared image reliably and accurately in real time. According to the technical scheme, the method comprises the following steps of: reading an infrared digital image which is shot from an outdoor scene into a computer program, and converting the image into a grayscale image; performing image segmentation, geometrical feature extraction, luminance feature extraction, edge contour extraction and piecewise linear feature extraction on the grayscale images by an image extraction program, and dividing the image into a target region and a background region; counting and identifying geometrical features, luminance features and piecewise linear features in the regions automatically by a feature comprehensive analysis and identification module, scanning and screening one by one, and removing suspected targets which do not have the infrared image feature of the high-voltage wire to obtain initial pixels of the image of the overhead high-voltage wire; and outputting and displaying the acquired final pixels of the image of the overhead high-voltage wire by a high-voltage wire pixel marking output module.
Owner:10TH RES INST OF CETC
Three-dimensional image quality evaluation method based on gradient information guided binocular view fusion
ActiveCN107578403AImprove accuracyImprove robustnessImage enhancementImage analysisIntermediate imageImaging quality
The invention discloses a three-dimensional image quality evaluation method based on gradient information guided binocular view fusion. According to the method, a Sobel operator and a LoG operator areutilized to construct a united statistical gradient map which serves as a weight map for binocular view fusion, and a corresponding intermediate reference image and a corresponding intermediate distortion image are obtained; then, image feature information extraction is performed on the intermediate images, wherein image feature information comprises edge information, texture information and contrast information, and depth information is extracted from a disparity map of a reference and distortion three-dimensional image pair; and last, a final image quality objective evaluation score is obtained through measurement of a feature similarity and SVR-based feature integration and quality mapping, and measurement of three-dimensional image quality loss is realized. Experiment results show that an algorithm proposed based on the method has good accuracy and robustness.
Owner:ZHEJIANG UNIV
Real-time robustness tracking device of moving target or dim small target under complex background
InactiveCN102332165ADiversity guaranteedReduce the amount of calculationImage enhancementImage analysisLow contrastGray level histogram
The invention relates to a real-time robustness tracking device of a moving target or a dim small target under a complex background, a target image preprocessing unit of the device is used for performing preprocessing on an input image; a histogram statistical unit is used for performing calculation and processing to get a gray level histogram of the image; a calculation gray level image feature unit is used for calculating the difference delta x between the maximum gray level value xmax and the non-zero minimum gray level value xmin in the gray level histogram and calculating the different delta y between the number of pixels ymax of the maximum gray level value and the number of the pixels ymin of the non-zero minimum gray level value; a judging unit is used for autonomously judging whether the image belongs to the low-contrast dim small target situation or the complex background condition situation according to the delta x and the delta y; and then the device is used for autonomously deciding the adoption of the corresponding tracking method to perform target tracking and output the tracking result. The two features, namely the contrast and the gray level complexity, which can effectively represent the image in the gray level histogram of the image are adopted for comprehensive judgment, and then the great judgment result can be obtained.
Owner:CHANGCHUN INST OF OPTICS FINE MECHANICS & PHYSICS CHINESE ACAD OF SCI
Computer-executed text risk prediction method and apparatus
ActiveCN109299228AImprove accuracyNatural language data processingText database queryingPart of speechFeature synthesis
Owner:ADVANCED NEW TECH CO LTD
Method for classifying imbalance heart beats based on multi-module neural network
InactiveCN109645983AEliminate low frequency noiseEliminate high frequency noiseDiagnostic recording/measuringSensorsEcg signalFeature extraction
The invention discloses a method for classifying imbalance heart beats based on a multi-mode neural network. The method involves an electrocardiosignal preprocessing module, an imbalance data processing module and a feature extracting and classifying module. The preprocessing module conducts denoising and segmenting on an electrocardiosignal; the imbalance data processing module is a core of a system, and sequentially introduces three kinds of methods for processing imbalance in combination with the features of the electrocardiosignal and the features of an algorithm, wherein the methods include boundary sample feature linear synthesis (BLSM), a context feature comprehensive module (CTFM) and a two-phase training (2PT); the feature extracting and classifying module obtains high-order features of all categories of heart beats and realizes final heart beat classification. The method has the advantages that in the prior art, the heart beats cannot be well classified, the corresponding solutions are provided from the aspects of sampling, features and algorithms, and therefore the accuracy of classifying is improved. The method is suitable for solving of the problem of classifying imbalance of time sequence data, images and others, and has generality.
Owner:NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
Zero-sample cross-modal retrieval method based on multi-modal feature synthesis
ActiveCN111428071ASolving insufficient sample sizeEasy to learnMetadata text retrievalCharacter and pattern recognitionSemantic spaceSemantic feature
The invention discloses a zero-sample cross-modal retrieval method based on multi-modal feature synthesis. The method comprises the steps: employing two adversarial generative networks, synthesizing feature representations of different modals through class embedding shared by two modal data, then mapping original modal data and synthesized modal data to a common subspace, and carrying out the aligned distribution of the original modal data and the synthesized modal data. Therefore, the relation between different modal data of the same category is established, and knowledge is migrated to unseen categories. The cyclic consistency constraint further reduces the difference between the original semantic feature and the reconstructed semantic feature, and well establishes the association between the original representation and the semantic feature in each modal, so that the common semantic space is more robust, and the accuracy of zero-sample cross-modal retrieval is improved.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA
Method for distinguishing fog concentration in intelligent image monitoring of power transmission line
InactiveCN109961070AAccurate identificationHigh concentration classification accuracyCharacter and pattern recognitionSynthesis methodsSample image
The invention discloses a method for distinguishing fog concentration in intelligent image monitoring of a power transmission line, which adopts a multi-feature synthesis method and comprises the following steps of: extracting a plurality of features related to fog in a picture, and synthesizing the plurality of features extracted from each image into a feature parameter table to form a two-dimensional feature map; utilizing a deep learning convolutional neural network to train and model the characteristic parameter graphs of a large number of sample images; and judging whether the unknown image has fog or not by using the trained model, and distinguishing the concentration levels of the fog, namely clear fog, medium fog and dense fog. According to the method, a plurality of deep and irrelevant features of the provider are integrated to serve as image feature parameters, and then a nonlinear classification algorithm model is trained for a large number of sample images by using the convolutional neural network, so that the problem that the accuracy of detecting whether the image is foggy is low is solved.
Owner:STATE GRID HEBEI ELECTRIC POWER RES INST +2
Computer-assisted ultrasonic diagnosis method for left atrium/left auricle thrombus
ActiveCN103646135AAccurate acquisitionReduce subjective judgmentSpecial data processing applicationsResearch ObjectSonification
The invention discloses a computer-assisted ultrasonic diagnosis method for a left atrium / left auricle thrombus. The technical scheme includes that data mining technology, a pattern recognition theory and medical clinical information are combined, a gray-scale video and a real-time three-dimensional dynamic video serve as research objects, all-dimensional information in an image is accurately acquired, potential disease association rules in the image information are mined, and multiclass characteristics are comprehensively analyzed to obtain a detection method for automatically detecting and classifying the left atrium / left auricle thrombus. A thrombus recognition method can avoid missed diagnosis and misdiagnosis caused by subjective reasons such as inadequate experience or visual fatigue of doctors, and patients with suspected left atrium / left auricle thrombi clinically detected by transesophageal echocardiography can be confirmed as early as possible, so that the patients without thrombosis can receive cardioversion treatment of atrial fibrillation as early as possible. The method is simple and convenient to operate and high in practicability, and has important guiding significance for diagnosis and treatment of the left atrium / left auricle thrombus and ventricular fibrillation.
Owner:HARBIN MEDICAL UNIVERSITY
Zero sample target classification method based on pseudo sample feature synthesis
InactiveCN110309875AGuaranteed richnessAvoid domain drift problemCharacter and pattern recognitionFeature vectorSemantic vector
The invention provides a zero sample target classification method based on pseudo sample feature synthesis. The method comprises the following steps of obtaining the samples and the annotation information of other categories similar to a category to be identified; secondly, obtaining the semantic descriptions of a visible class and a non-visible class by means of network capture and the like, andconverting the class description information into the semantic vectors through a natural semantic processing model; calculating a similarity score between each unseen class and each visible class; constructing a convolutional neural network classification model, wherein the model is divided into a feature extraction part and a classification part; for each unseen class, screening N visible classeswith highest scores according to the similarity scores, randomly selecting the samples, and inputting the samples into a feature extraction network to obtain the feature vectors; combining the feature vectors of the N visible classes according to the similarity score to serve as the feature vectors of the unseen classes; training the classification network by using the unseen feature vectors, sothat the samples of the category can be accurately identified under the condition that there is no available training samples of a certain category of to-be-identified targets.
Owner:HARBIN ENG UNIV
Digital Ink Database Searching Using Handwriting Feature Synthesis
InactiveUS20120239397A1Still image data retrievalCharacter and pattern recognitionHandwritingFeature vector
A method of searching a digital ink database is disclosed. The digital ink database is associated with a specific author. The method starts by receiving a computer text query from an input device. The computer text query is then mapped to a set of feature vectors using a handwriting model of that specific author. As a result, the set of feature vectors approximates features that would have been extracted had that specific author written the computer query text by hand. Finally, the set of feature vectors is used to search the digital ink database.
Owner:SILVERBROOK RES PTY LTD
Three-dimensional point cloud map fusion method based on vision correction
ActiveCN107818598AReduce the number of iterationsIncrease success rateImage enhancementImage analysisPoint cloudWeight coefficient
The invention discloses a three-dimensional point cloud map fusion method based on vision correction, which comprises the steps of 1) processing two point cloud maps to be fused; 2) extracting 3D-SIFTkey points of the two three-dimensional point cloud maps; 3) extracting an IPFH feature on the 3D-SIFT key points; 4) searching feature matching points through calculating the Euclidean distance between the feature points; 5) calculating a conversion matrix, and rotating the point cloud maps; 6) and fusing the two point cloud maps together by adopting an ICP algorithm. According to the invention,the SIFT feature is expanded to three-dimensional point clouds, the 3D-SIFT key points are extracted, and thus the robustness of the feature for view angle rotation and conversion is ensured; a problem that the weight coefficient of an original FPFH feature is incorrect is overcome through extracting the IPFH feature, and meanwhile, the feature integrates geometric characteristics of neighborhoodpoints to represent features of a three-dimensional point, so that the stability of the algorithm is greatly improved. Two three-dimensional point cloud maps which are greatly different in view anglecan be fused together according to the processing.
Owner:西安电子科技大学昆山创新研究院
Video quality evaluation method and device, video processing device and medium
ActiveCN110121110AOvercoming shortcomings in quality assessmentEffective Video Quality Assessment ResultsSelective content distributionNeural network systemManual annotation
The invention discloses a video quality evaluation method and device, a video processing device and a medium. The video quality evaluation method comprises the following steps: constructing a trainingdata set of an evaluation model to be used for a neural network system, wherein the training data set comprises manual annotation data and user click rate data; an attribute feature obtaining step: for each sample in the training data set, obtaining each attribute feature, related to the video attribute data, of each sample through a neural network system; a feature synthesis step: for each sample, performing feature synthesis processing on each attribute feature of the sample to obtain a synthesis feature of the sample; and a training step: performing confrontation training on the syntheticfeatures of each sample by combining the manual annotation task and the user click rate task, and generating an evaluation model for evaluating the video quality. According to the video quality evaluation model provided by the invention, a more accurate and effective evaluation result can be obtained for a new video or an exposed video.
Owner:BEIJING QIYI CENTURY SCI & TECH CO LTD
Composite texture feature extraction method for flotation froth image
ActiveCN105405149AFully reflectFully describe structural propertiesImage enhancementImage analysisFeature extractionMineral flotation
The present invention discloses a composite texture feature extraction method for a flotation froth image. The method comprises: firstly, in a grayscale quantization matrix of a froth image, acquiring a face neighborhood set of all central pixel points; then, for all the central pixel points, constructing a three-dimensional data table and obtaining a nested grayscale frequency table; again, acquiring an improved neighborhood grayscale correlation matrix; and finally, obtaining a new composite texture feature, wherein the feature integrates a size, a texture and a roughness degree of froth, and has relatively high stability and separability in reflecting a texture of flotation froth; and according to the extracted composite texture feature, it is easy to distinguish flotation froth images with different operating conditions in different ore grades, thereby having a relatively high accuracy rate of recognizing operating conditions. The composite texture feature extraction method for the flotation froth image provided by the present invention is simple and effective, and is very important to guide the recognition of froth operating conditions in a mineral flotation site.
Owner:CENT SOUTH UNIV
Digital ink database searching using handwriting feature synthesis
InactiveUS8219908B2Still image data retrievalDigital data processing detailsFeature vectorHandwriting
A system and method for ink database searching using handwriting feature synthesis is disclosed which allows a digital ink database to be searched using a text-based query. Using a writer-specific handwriting model derived from a handwriting recognition system or suitable training procedure, a text query is converted into feature vectors that are similar to the feature vectors that would have been extracted had the author of the digital ink database written the text query by hand. The feature vectors are then used to search the database.
Owner:SILVERBROOK RES PTY LTD
Speech recognition method and device, electronic equipment and storage medium
ActiveCN113823262AEfficient and accurate identificationRealize identificationSpeech recognitionNeural learning methodsFeature extractionSpeech Acoustics
The invention relates to the technical field of speech recognition, in particular to a speech recognition method and device, electronic equipment and a storage medium, which can be applied to various scenes such as cloud technology, artificial intelligence, intelligent traffic and auxiliary driving and are used for efficiently and accurately realizing speech recognition of multiple dialect target languages. The method comprises the following steps: acquiring to-be-recognized voice data of a target language; extracting voice acoustic features corresponding to each frame of voice data in the to-be-recognized voice data; performing deep feature extraction on the voice acoustic features to obtain corresponding dialect embedding features; encoding the voice acoustic features to obtain corresponding acoustic encoding features; and based on the dialect embedding feature and the acoustic coding feature, performing dialect speech recognition on the to-be-recognized speech data to obtain target text information and a target dialect category corresponding to the to-be-recognized speech data. According to the method, the dialect embedding feature and the acoustic coding feature are combined for comprehensive learning, so that speech recognition for recognizing various dialects can be efficiently and accurately realized.
Owner:TENCENT TECH (SHENZHEN) CO LTD
Scene complexity evaluation method based on gradient boosting decision tree model
PendingCN111797000AClear Concise Complexity EstimationMeet the selected needsSoftware testing/debuggingData setFeature parameter
The invention provides a scene complexity evaluation method based on a gradient boosting decision tree model, and the method comprises the following steps: S1, collecting parameters, and generating asimulation driving scene; S2, performing complexity scoring on the simulated driving scene sample; S3, inputting the summarized complexity characteristic elements into a decision tree model for calculation; S4, upgrading the decision tree; S5, obtaining a characteristic parameter data set influencing the model, taking 80% of the data set as a training set and 20% of the data set as a test set, andadopting 5-fold cross validation debugging to obtain a complexity evaluation model; S6, calculating scene complexity of the to-be-evaluated data; and S7, splitting the input driving scene data into dynamic features and static features, and performing comprehensive scoring according to each influence feature to obtain scene complexity. According to the method, a clear and simple complexity estimation value of the automatic driving test scene can be given, and the requirement that a tester can select the driving scene according to the complexity of the scene is met.
Owner:BEIJING CATARC DATA TECH CENT +2
Video copy detection method based on time-domain visual attention
InactiveCN102929970ACharacter and pattern recognitionSpecial data processing applicationsTime domainFeature synthesis
The invention provides a video copy detection method based on time-domain visual attention. The method comprises the following steps of: acquiring visual attention changes between different video frames according to a visual attention mechanism, and acquiring representation of time-domain attention degree; calculating a time-domain attention weight of a video frame in a video clip according to the time-domain attention degree to form a visual attention transfer image of the video clip; and finally, extracting video hash on the generated visual attention transfer image provided with time domain and space domain information. By the method, the time domain information of the video is fully considered, a video frame which makes the video content prominent is weighted, the time domain and space domain information is integrated through the extracted characteristics, and the video copy detection method has high robustness on time domain attacks.
Owner:SHANDONG UNIV
Vision-based object detection by part-based feature synthesis
A method is provided for training and using an object classifier to identify a class object from a captured image. A plurality of still images is obtained from training data and a feature generation technique is applied to the plurality of still images for identifying candidate features from each respective image. A subset of features is selected from the candidate features using a similarity comparison technique. Identifying candidate features and selecting a subset of features is iteratively repeated a predetermined number of times for generating a trained object classifier. An image is captured from an image capture device. Features are classified in the captured image using the trained object classifier. A determination is made whether the image contains a class object based on the trained object classifier associating an identified feature in the image with the class object.
Owner:GM GLOBAL TECH OPERATIONS LLC
Wireless channel characteristic comprehensive information fusion method
ActiveCN104301100AIncrease spawn rateIncreased information complexityKey distribution for secure communicationFeature extractionCommunications system
Owner:CHINA ACAD OF LAUNCH VEHICLE TECH
Machine learning model construction method and computer readable storage medium
ActiveCN110569904AIncrease the number ofImprove forecast accuracyWeb data indexingCharacter and pattern recognitionMinority classBusiness data
The invention discloses a machine learning model construction method and a computer readable storage medium. The method comprises the following steps: acquiring auxiliary data according to a preset keyword; obtaining business data, and determining data items corresponding to the input items and data items corresponding to the output items; performing label marking on the business data of which thevalues of the data items corresponding to the output items are not empty; obtaining a first sample according to the service data; obtaining service data with label marks in the first sample as a second sample; synthesizing feature items through a feature synthesis technology, and merging the feature items into a second sample as input items; performing positive and negative sample equalization processing on the second sample through a synthetic minority class oversampling technology, and taking newly synthesized sample data as a third sample; combining the second sample and the third sample to obtain a fourth sample; and training the fourth sample through a preset machine learning algorithm to obtain a machine learning model. According to the invention, the accuracy of the machine learning model can be improved.
Owner:FUJIAN RONGJI SOFTWARE
Self-learning emotion interaction method based on multi-modal recognition
ActiveCN112083806AMeeting specific emotional needsImprove interactive experienceInput/output for user-computer interactionCharacter and pattern recognitionFeature extractionInteraction interface
The invention discloses a self-learning emotion interaction method based on multi-modal recognition. The method comprises the following steps: respectively collecting voice, face and gesture signals by a non-contact channel; performing feature extraction on the signals to obtain preliminary features of the signals; inputting the features into a bidirectional LSTM layer to obtain single-mode private information and multi-mode interaction information, and obtaining fusion features according to the information; predicting the emotion of a user based on a classification learning algorithm in combination with the multi-modal fusion features and a historical emotional state curve, and selecting an interaction mode; in the interaction mode, giving an interaction response according to the dialoguememory network; and finally, feeding back and optimizing the emotional state curve and the dialogue memory network according to the interaction effect. According to the method, an operator is allowedto input information through multiple channels of a non-contact man-machine interaction interface, multi-modal fusion features are comprehensively considered, and an interaction task is completed incombination with the historical emotional state and the dialogue memory network.
Owner:SOUTH CHINA UNIV OF TECH
Vision-Based Object Detection by Part-Based Feature Synthesis
ActiveUS20120257819A1Increase the number ofCharacter and pattern recognitionObject basedVision based
A method is provided for training and using an object classifier to identify a class object from a captured image. A plurality of still images is obtained from training data and a feature generation technique is applied to the plurality of still images for identifying candidate features from each respective image. A subset of features is selected from the candidate features using a similarity comparison technique. Identifying candidate features and selecting a subset of features is iteratively repeated a predetermined number of times for generating a trained object classifier. An image is captured from an image capture device. Features are classified in the captured image using the trained object classifier. A determination is made whether the image contains a class object based on the trained object classifier associating an identified feature in the image with the class object.
Owner:GM GLOBAL TECH OPERATIONS LLC
Recognition method of electrocardiosignal based on DWNN framework
ActiveCN110613445AAchieve tight couplingTightly boundDiagnostic recording/measuringSensorsEcg signalWavelet decomposition
The invention discloses a recognition method of an electrocardiosignal based on a DWNN framework. An electrocardiogram enters a wavelet layer as original data, the wavelet layer is reconstructed through wavelet decomposition and random weighting, characteristics of deep-layer data in the electrocardiogram are extracted, a pooling layer reduces the dimension of the extracted data characteristics through pooling operation, a full connection layer synthesizes the data characteristics after dimensionality reduction, and an output layer uses a softmax function to output classification results. Among 800 tested electrocardiosignals, 794 electrocardiosignals are predicted correctly and 6 electrocardiosignals are predicted incorrectly by the recognition method, and the prediction accuracy of the recognition method is 99.25%; and the result shows that the recognition method has more obvious classification results and recognition results.
Owner:XIAN UNIV OF POSTS & TELECOMM
Space function unit-based land area province city and county space planning three-region identification method
PendingCN107766825AImplement batch processingGuaranteed accuracyScene recognitionResourcesSpatial functionClassification rule
The invention discloses a space function unit-based land area province city and county space planning three-region identification method. The method comprises the steps of performing classification and grading on landforms by adopting refined DEM data; identifying a primary space function unit; extracting the space function unit; and determining a three-region classification rule and automaticallyclassifying and identifying three regions. By integrating element characteristics in the unified space function unit, the accuracy of three-region classification is ensured; and the three-region classification rule is modeled through a decision tree algorithm, and the automation of three-region classification definition is realized, so that the purposes of effectively and finely integrating and representing space and attribute characteristics of geographic elements on space units, accurately classifying the three regions, enabling the minimal space units to be independent mutually, homogeneous internally and stable structurally and improving working efficiency of space planning are achieved.
Owner:国家测绘地理信息局第一航测遥感院
A radar radiation source signal intra-pulse characteristic comprehensive evaluation method and system
ActiveCN109766926AFeature Evaluation PerfectIncreasing the SNR affects the significance indexWave based measurement systemsInternal combustion piston enginesFeature extractionFeature evaluation
The invention belongs to the technical field of radar radiation source signal characteristic evaluation in electronic countermeasure, and discloses a radar radiation source signal intra-pulse characteristic comprehensive evaluation method and system. The method comprises the following steps of firstly, carrying out feature extraction on a received radar radiation source signal, and carrying out feature evaluation index measurement and normalization according to an established evaluation system; carrying out improved interval analytic hierarchy process by combining expert priori knowledge and an actual environment, and establishing a nonlinear equation optimization model by using an improved projection pursuit algorithm; and finally, performing final subjective and objective decision fusionby using a projection spectrum gradient algorithm. The radar radiation source signal intra-pulse characteristic evaluation method and system can reasonably and effectively realize various radar radiation source signal intra-pulse characteristic evaluations based on an actual environment, and scientific and effective evaluation is carried out to help to select characteristics capable of highlighting radar radiation source signals so as to facilitate the subsequent radar radiation source signal sorting and identification.
Owner:XIDIAN UNIV
Identity recognition method and electronic equipment
InactiveCN110569707AImprove accuracyImage enhancementImage analysisPoor Quality ImageWeight coefficient
The embodiment of the invention relates to an identity recognition method and electronic equipment, and the method comprises the steps: obtaining a to-be-recognized image which comprises a face imageof at least one to-be-recognized person, and obtaining the face image of the to-be-recognized person based on the to-be-recognized image; acquiring face features of the to-be-recognized person based on the face image; obtaining a first weight coefficient of the face features; obtaining auxiliary features of the to-be-identified person; obtaining a second weight coefficient of the auxiliary features; according to the first weight coefficient and the second weight coefficient, combining face features and the auxiliary features to obtain recognition features of the to-be-recognized person; and matching the identification features of the to-be-recognized person with the identification features of the known identity to obtain the identity of the to-be-recognized person. The identification features are obtained by combining the face features and the auxiliary features of the to-be-identified person and the respective weight coefficients, the identity of the to-be-identified person can be comprehensively judged by combining multiple features, and the influence of poor face image quality on the identity identification effect is reduced, so that the accuracy of identity identification is improved.
Owner:深圳数联天下智能科技有限公司
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