59results about How to "Overcome ambiguity" patented technology

An optical device is described that may be used as a microscope system for real-time, three-dimensional optical imaging. The device includes a miniature, fiber optic, intra-vital probe microscope that uses a dual-axes confocal architecture to allow for vertical scanning perpendicular to a surface of the sample (e.g., a tissue surface). The optical device can use off-axis illumination and collection of light to achieve sub-cellular resolution with deep tissue penetration. The optical device may be used as part of an integrated molecular imaging strategy using fluorescence-labeled peptides to detect cell surface targets that are up-regulated by the epithelium and / or endothelium of colon and breast tumors in small animal models of cancer.

The invention provides a method for fusing multispectral and full-color images with light cloud. The problem that the cloud and mist area is interfered by a cloud layer after the multispectral and full-color images with light cloud are fused is mainly solved. The method comprises the following implementation steps of: sampling and filtering the multispectral image with light cloud, and obtaining background images of the multispectral and full-color images; respectively removing light cloud of the multispectral and full-color images with light cloud; performing PCA conversion on the multispectral image in which the cloud is removed, and performing Shearlet decomposition on the converted first principal component image and the full-color image; taking a low-frequency coefficient of the first principal component as a low-frequency coefficient of a fusion component, and taking a high-frequency coefficient of the full-color image as a high-frequency coefficient of the fusion component; and performing reversible PCA conversion on the fusion component and the other components subjected to the PCA conversion, and obtaining the fusion image. The method has the advantages of high definition of light cloud area of the fusion image and high spectrum retainability and can be used for military target recognition, weather and environment monitoring, land utilization, urban planning and prevention and reduction of natural disasters.

The present invention discloses a multispectral image and full-color image fusion method based on dual sparse non-negative matrix factorization and mainly solves the problems that space information is fuzzy and a spectrum is distorted in the prior art. The multispectral image and full-color image fusion method comprises the steps of: (1) respectively inputting a multispectral image with a low spatial resolution ratio, a full-color image with a high spatial resolution ratio, a spectrum degenerate matrix and a spatial degenerate matrix; (2) respectively carrying out partitioned column vectorization on the multispectral image with the low spatial resolution ratio and the full-color image with the high spatial resolution ratio; (3) carrying out dual sparse non-negative matrix factorization on the images subjected to column vectorization so as to obtain a dictionary with a high spatial resolution ratio and a coefficient matrix with spectral information; and (4) multiplying the dictionary with the high spatial resolution ratio by the coefficient matrix with the spectral information so as to obtain the multispectral image with the high spatial resolution ratio, which is subjected to column vectorization, and restoring the multispectral image with the high spatial resolution ratio, which is subjected to column vectorization, into the multispectral image with the high spatial resolution ratio. According to the multispectral image and full-color image fusion method disclosed by the present invention, the accurate space information and the accurate spectral information can be obtained; and the multispectral image and full-color image fusion method can be used for the fields of remote sensing of object identification, terrain classification, environmental monitoring and the like.

The present invention proposes and discloses a method for dynamically simulating a land future use scenario. The method integrates a capability that a cellular automaton (CA) simulates a complex systematic space-time evolution process and an advantage that a CLUE-S model simulates multiple types of land use type competitions; and the method overcomes certain inherent defects of a traditional CA or a pure CLUE-S model through advantage integration; in addition, intelligent computation of a distributional probability is realized by adopting an artificial neural network (ANN) algorithm; synchronous simulation of multiple land use changes is realized by introducing a competition mechanism of a roulette, so that the new method is more suitable for multiple types of land use data; and moreover, compared with a traditional model, the method has the practical advantages of higher precision, suitability for multiple scales, low data demand, few parameters, simple and convenient operation, high speed and the like. According to the method for dynamically simulating the land future use scenario, the intelligent algorithm (ANN) and the uncertainty model (the roulette) are effectively combined; and the method is applied to the prediction of the land future use scenario.

The invention discloses an image multi-target joint segmentation method based on multi-tag multi-sample learning, comprising the following steps: first, performing object detection on an input image set to get a candidate object set, and performing segmented object clustering on the candidate object set to get accurate object tags; the, performing salience detection and binary segmentation on the input image set to get a salient region, transferring the object tags in the candidate object set to the salient region, and performing super pixel segmentation on the salient region to get a salient region containing tags; and finally, using an integrated multi-sample multi-tag learning method based on feature random selection to get the object tag of each super pixel in the salient region, thus completing joint segmentation of the input image set.

The invention specifically discloses a condition diagnosis system for transformer fault types, belonging to the technical field of condition monitoring and fault diagnosis of power equipment. The condition diagnosis system comprises an oil sample collection module, an oil-gas separation module, a gas separation module, a gas detection module, a data processing module and a data transmission module. The condition diagnosis system provided by the invention successfully realizes rapid, accurate and real-time detection of the composition and concentrations of dissolved gases in the insulating oil of a transformer, avoids the shortcoming of lack of monitoring means with long-term stability and credible precision in the operation and maintenance of the transformer, and provides reliable data for online evaluation and analysis of the operating state and remaining life of the transformer; and a sample retrieval algorithm based on Euclidean distance is innovatively introduced for identification of fault types, so the condition diagnosis system overcomes problems in fuzziness and applicability of data about dissolved gases in the insulating oil, is improved in accuracy and timeliness of fault recognition, and achieves the goal of comprehensive optimization of risks, efficiency and cost in power safety production.

The invention belongs to the underwater sound direction-finding field and relates to a sound pressure and vibration velocity cross-spectrum method-based vector array port and starboard discrimination method. The method includes the following steps that: step (1) after received sound pressure signals are converted into frequency-domain signals, frequency-domain broadband conventional beamforming processing is carried out on the frequency-domain signals, so that an original spatial spectrum matrix can be obtained, wherein the spatial spectrum matrix is a matrix of an outputted spatial spectrum type; step (2) bidirectional one-order recursive filtering processing is performed on the obtained original spatial spectrum matrix, so that a smoothed spatial spectrum can be obtained; and step (3) according to the smooth spatial spectrum, DT decibels are increased based on the smooth spatial spectrum, so that a threshold for spectral peak screening can be obtained. According to the method of the invention, peak screening is carried out on the spatial spectrum; direction estimation is carried out on signals in a spectral peak range; subtractive suppression is carried out on pseudo peak measurement through comparing an estimated result with a spectral peak position; and therefore, the problem of port-starboard ambiguity under a low signal-to-noise ratio can be solved, and weak target detection under a homogeneous noise background can be improved.

A system allows related documents to be retrieved using conventional search engines while overcoming the ambiguity of a search key entered by the user. The system includes a word sense associative network display portion for displaying word senses of the search key entered by the user together with related word senses in a network, a search portion for conducting a search by generating a search key based on word senses selected by the user, and a filtering portion for selecting documents from the result of the search that matches the selected word sense.

Disclosed herein is a multi-entity-centric integrated search system and method. The multi-entity-centric integrated search system includes an entity information acquisition server for receiving and analyzing a query term and determining entities and types of entities, and an integrated search result provision server for configuring an integrated search results page using results acquired from unit service calling units, such as an external API calling unit, a search engine calling unit, and an inference engine calling unit, and presenting integrated search results. The present invention is advantageous in that precise search results can be shown more rapidly, satisfaction with search results for a query term in which multiple entities coexist can be improved, the ambiguity of query terms is overcome, and an open platform capable of operating in conjunction with various types of web services is provided.

The invention discloses an anti-shaking method and an anti-shaking device for portable equipment, and belongs to the technical field of image processing. The method and the device solve the problem that a user feels uncomfortable because pictures of the portable equipment shake in the playing and displaying process due to external influence in the prior art. The corresponding method comprises the following steps of: acquiring shaking variation of the portable equipment in a predetermined time interval; and converting the shaking variation into correcting value, and performing corresponding correcting operation and displaying the displayed contents of the portable equipment according to the correcting value. After the shaking variation of the portable equipment is converted into the correcting value based on the predetermined time interval, the correcting value is directly acted on the real-time displayed contents, so that displacement change of display images or characters relative to a user due to movement of the equipment is counteracted, and the problem that the displayed contents are blurry due to equipment shake caused by the external influence in the playing and displaying process of the portable equipment is solved.

The invention belongs to the mobile communication technological field and discloses an array antenna-based target signal source detection method. The method includes the following steps that: the number and orientations of target signal sources are judged preliminarily though a beamforming technology, and an antenna coverage area is divided into a plurality of cells according to received signal power obtained in a beam rotation process; a beam is made to sequentially direct to the plurality of cells, and the spatial spectrum of signals in each of the cells is obtained through an MUSIC algorithm, and the number and orientations of target signal sources in each of the cells are determined; and the calculation results of the plurality of cells are summarized, and the exact number and preciseorientations of the target signal sources are obtained after comprehensive processing is carried out. With the array antenna-based target signal source detection method of the invention adopted, the problems of low spatial resolution and many limitations in application of target signal source orientation estimation in the prior art can be solved; and spatial resolution can be improved, and the number of signal sources that can be detected is not affected by the number of array antenna array elements.

The invention provides a method and device for evaluating fluid factors based on rock physical models. The evaluation method comprises the following steps: acquiring the physical property parameter information of rock in a researched work area; calculating the elastic parameters of a sandstone reservoir under the conditions different porosity and saturation of different fluids based on a White model by using input rock physical property parameters; selecting a plurality of conventional reservoir fluid factors in combination with the researched work area and carrying out analysis and evaluation; constructing porosity-fluid factor domain rock physical models corresponding to different fluid factors based on the calculated elastic parameters; and performing evaluation based on the rock physical models so as to obtain an optimal reservoir fluid factor. The optimal fluid factor selected by using the method of the invention can adapt to the fluid detection tasks of reservoirs of different pore development types; and the method overcomes the problems of limitation and multiple solutions of conventional fluid factor evaluation methods, and improves the accuracy of fluid detection and the precision of reservoir prediction.

The invention discloses an emotional bandwidth determination method and an emotional damage judgment method, and relates to the fields of cognitive science and cognitive psychology. Emotional bandwidth refers to the range of the magnitude of emotional experience of a cognitive individual induced by external stimulation, and comprises positive emotional bandwidth, negative emotional bandwidth and positive-negative emotional bandwidth. The emotional bandwidth determination method comprises the following steps: making a tester watch positive, neutral and negative picture tasks for 8-10 seconds respectively, and acquiring information about each viewing point by using an eye movement device at the same time; calculating the diameters of the pupils of the tester while watching the positive, neutral and negative picture tasks; calculating the positive emotional bandwidth (positive-neutral), negative emotional bandwidth (negative-neutral) and positive-negative emotional bandwidth (positive-negative) of the tester. The concept of emotional bandwidth is put forward for the first time, the fuzziness and uncertainty of the conventional emotional experience psychological measurement are eliminated, and an objective standard of emotional experience as well as the emotional damage judgment method are provided.

An optical device is described that may be used as a microscope system for real-time, three-dimensional optical imaging. The device includes a miniature, fiber optic, intra-vital probe microscope that uses a dual-axes confocal architecture to allow for vertical scanning perpendicular to a surface of the sample (e.g., a tissue surface). The optical device can use off-axis illumination and collection of light to achieve sub-cellular resolution with deep tissue penetration. The optical device may be used as part of an integrated molecular imaging strategy using fluorescence-labeled peptides to detect cell surface targets that are up-regulated by the epithelium and / or endothelium of colon and breast tumors in small animal models of cancer.

The invention relates to a virtual reality head-mounted device based on a Unity3D engine. The virtual reality head-mounted device based on the Unity3D engine comprises a rectangular solid shell, wherein a display screen is fixed in the rectangular solid shell and displays pictures obtained by two cameras through a computer, the side, opposite to the display screen, of the device is of a dual-hole structure, lenses used for focusing are placed in the dual-hole structure, and the Unity3D engine is adopted for the computer so that the pictures displayed on the display screen can generate binocular tube type distortion which counteracts distortion generated by the lenses. According to the virtual reality head-mounted device based on the Unity3D engine, the blur effect of the pictures is eliminated due to the powerful software function of the Unity3D engine, and the requirement of a user is greatly met.

The invention relates to a method and a system for measuring plant leaf area based on color calibration. The method comprises the following steps: adopting a camera to collect an initial image of a leaf to be measured on a white calibration board, and extracting a measurement area image according to the initial image; performing color calibration on the measurement area image to obtain a difference matrix between the measurement area image and the ideal image of the leaf to be measured, and obtaining the ideal image according to the difference matrix; performing image processing on the ideal image to obtain pixel points of a leaf image in the ideal image; calculating the area of the leaf to be measured according to a pixel point of the leaf image and an actual area of the measurement areaimage on the white calibration board. The method of the invention inherits the advantages of the image measurement method, eliminates the interference of the environmental illumination factor, is fast, and has high environmental adaptability, high stability and high precision.

The invention discloses a face recognition method based on an intelligent security and protection robot under an unlimited condition, and the method comprises the steps: carrying out the face detection of an image through employing the HOG features, and extracting a face region image for the subsequent processing; secondly, training a classifier for performing binary classification on the clear image and the blurred image by utilizing the CNN convolutional neural network, performing deblurring processing on the classified blurred image, and skipping the step of the clear image; then, carryingout deblurring processing on the moving image frame sequence by using a Lucy-Richardson algorithm; normalizing the image to the same size scale by using an SRCNN image super-resolution algorithm; inputting the image processed by the above steps into a trained CNN convolutional neural network to extract a feature vector; and finally, classifying the extracted feature vectors through an SVM, therebyrealizing face recognition. The method has the advantage that the efficiency and precision of face recognition of the intelligent security and protection robot in the patrol process are effectively improved.

The invention provides a method of constructing a rice molecular marker map based on competitive allelic PCR and an application in rice molecular breeding thereof, and belongs to the technical field of agriculture. The method aims to search for SNP sites by whole gene recombination sequencing of rice and mining SNP data of recombination sequencing; 565 SNP sites needed for breeding are obtained through combining existing SNP databases based on the SNP sites; the selected 565 SNP sites are utilized to perform molecular marking, and the rice molecular marker map is constructed. Physical locationof SNP markers of the rice molecular marker map constructed by the method is clear, detection method is simple. The rice molecular marker map can be directly used for partial molecular identificationand genetic background analysis of important agronomic traits, and has important application value to improve the efficiency of the rice molecular breeding.

The embodiment of the invention discloses a chromatography static correction processing method and device; the method comprises the following steps: inverting the nerve network of an initial velocitymodel so as to obtain the first near-surface velocity model; ray tracking the first near-surface velocity model according to small grid units, and calculating the ray degree of covering of the small grid units; discretizing the first near-surface velocity model on the basis of variable-grid unit according to the small grid unit ray degree of covering, wherein the difference value between the ray degrees of covering of two random grid units in the first near-surface velocity model after the variable-grid unit discretization is smaller than the first threshold; inverting the nerve network of thefirst near-surface velocity model after the variable-grid unit discretization, thus obtaining the second near-surface velocity model; determining the static correction amount according to the secondnear-surface velocity model. Various embodiments of the invention can improve the chromatography static correction processing precision and stability.

The invention discloses a fluorescent quantitative PCR (Polymerase Chain Reaction) qualitative detection method for yak-derived fiber composition. The fluorescent quantitative PCR qualitative detection method comprises the following steps of: performing PCR amplification with the DNA (Deoxyribonucleic Acid) of yakwool as a template, and detecting fluorescent signals of amplification products, wherein a reaction system for the PCR amplification contains a specific primer pair for amplification of yak-derived fiber composition and specific probes for the yak-derived fiber composition. The fluorescent quantitative PCR qualitative detection method can be used for easily and quickly detecting and identifying whether the yak-derived fiber composition exists in textiles or not; and due to the good specificity and excellent sensitivity of the designed specific primer pairs and specific probes, the method can be used for detecting yakwool with proportion being 1%(wt).

The invention provides a well logging interpretation method and device for predicting a sandstone hydrocarbon reservoir. The method comprises the steps: acquiring rock matrix physical property parameters and logging curve data; calculating longitudinal wave velocity, transverse wave velocity and density based on the rock matrix physical property parameters; constructing a sandstone hydrocarbon-bearing reservoir prediction factor, wherein the expression of the prediction factor comprises longitudinal wave velocity, transverse wave velocity and density; calculating and analyzing sandstone hydrocarbon-bearing reservoir prediction factor distribution characteristics based on the longitudinal wave velocity, the transverse wave velocity and the density, and determining a sandstone hydrocarbon-bearing reservoir prediction threshold; calculating a sandstone hydrocarbon-bearing reservoir prediction factor curve by utilizing the logging curve data, and predicting the hydrocarbon-bearing reservoir according to the sandstone hydrocarbon-bearing reservoir prediction threshold. The device comprises a data acquisition unit, a speed density calculation unit, a sandstone hydrocarbon-bearing reservoir prediction factor construction unit, a hydrocarbon-bearing reservoir prediction threshold analysis unit and a sandstone hydrocarbon-bearing reservoir prediction unit. The method overcomes the singleness and multiplicity of predicting the fluid only by resistivity information.

The invention discloses a method and device for detecting hydrocarbon-containing pores in a reservoir. The method comprises the steps that the longitudinal wave impedance data and shear wave impedancedata of a work area are acquired; a hydrocarbon-containing pore factor of the reservoir is constructed according to the longitudinal wave impedance data and the shear wave impedance data; and hydrocarbon-bearing pore detection of the reservoir is carried out according to the hydrocarbon-containing pore factor of the reservoir. According to the invention, the multiplicity and limitation of a conventional reservoir prediction method can be overcome, and the accuracy of reservoir prediction is improved.

The invention discloses a grading evaluation method for explodability of a step rock mass of an open-pit mine rock. Selecting rock mass explosibility grading indexes, determining a rock mass explosibility grading standard, respectively calculating digital characteristic expectation Ex, entropy En and hyper-entropy He of the cloud corresponding to each explosibility grading index, writing a forwardnormal cloud generator, and generating a cloud model of each explosibility grading index belonging to each rock mass explosibility grade; selecting a rock mass sample for measurement, and calculatingthe determinacy of each explodability grading index belonging to each explodability grade; counting the sample data to obtain the comprehensive weight of each explodability grading index; synthesizing the determinacy of each explosibility grade and the comprehensive weight of each explosibility grading index, calculating the comprehensive determinacy of the rock mass belonging to each explosibility grade, obtaining an explosibility grade determinacy model, and further determining the explosibility grade of the rock mass; grading end. According to the method, the defects of fuzziness and randomness of rock mass explodability grading in an existing explodability grading method can be overcome, and a grading result with high accuracy and reliability is provided.

The invention discloses a freight car number identification system based on image processing. The system conducts identification through the following steps that 1, a car number is positioned, wherein collected video images or static pictures are subjected to filtering, boundary enhancement and other processing, and the position of the car number is found automatically in the collected carriage image; 2, the images are preprocessed, wherein the car number image is subjected to graying, equalization, edge processing, binarization and other processing to make preparation for work in the next step; 3, characters are divided, wherein a car number area is divided into individual character areas to make preparation for character identification and solve the problems of ambiguity, character breakage and the like; 4, the characters are identified, and the process is a pattern recognition process.

The present invention provides an online detection method of cracks of an air channel insulation encapsulated layer of a dry-type hollow shunt reactor. The method mainly comprises the following stepsof: S01: reading endoscope detection image video of a detected dry-type hollow shunt reactor, and decomposing the endoscope detection image video into frames; S02: employing a local multi-scale dark channel endoscope image enhancement algorithm to perform enhancement and denoising operations of the images decomposed into the frames; S03: performing filtering processing of each image by employing wavelet multi scales taking the consideration of the dark channel priori criteria and same translucent color ratio assumption balance, and performing graying processing of each image; S04: employing alocal binary pattern operator according to local properties of endoscope image fracture distribution and gray contract to achieve dry-type hollow shunt reactor air channel insulation encapsulated layer crack edge detection and identification; and S05: determining crack positions of the dry-type hollow shunt reactor air channel insulation encapsulated layer. The method provided by the invention canaccurately achieve positioning of the cracks of the air channel insulation encapsulated layer.

The invention discloses an image denoising method based on a Contourlet transformation self-adaptation direction threshold value, and belongs to the technical field of images. An elliptical direction neighborhood consistent with a sub-band energy gathering direction is adopted to calculate the self-adaptation direction threshold value. The method comprises the steps that (1), an image with noise I is input; (2), Contourlet transformation is carried out on the I; (3), local signal direction energy of a coefficient is estimated through the elliptical direction neighborhood; (4), a direction energy factor of the coefficient is calculated according to the local signal direction energy and dimension signal average energy; (5), based on the Bayes criterion, a Bayes threshold value is corrected through the direction energy factor to obtain the self-adaptation direction threshold value; (6), based on soft threshold value rules, threshold value shrinkage is carried out on the coefficient with noise through the self-adaptation direction threshold value; (7), Contourlet inverse transformation is carried out through the shrunk coefficient to obtain a denoised image. The method can effectively remove the noise, and clear image details can be kept.

The invention discloses an active power distribution network power supply quality composite sensing and evaluating method and system based on ubiquitous interconnection. The method comprises the following steps: collecting power supply quality measurement data of a plurality of monitoring points in an active power distribution network, and carrying out the fusion of the data of each monitoring point based on a DS evidence theory; realizing composite sensing of the power supply quality condition of each part in the active power distribution network to obtain a power supply quality index composite sensing sequence; and performing comprehensive evaluation on the power supply quality composite perception sequence in combination with a cloud model theory, so that randomness and fuzziness of power supply quality evaluation are overcome, and finally a comprehensive, accurate and objective power supply quality index evaluation result of the active power distribution network is given. Accordingto the method, comprehensive, accurate and objective composite perception of the power supply quality in the active power distribution network can be realized, and the comprehensive evaluation resultof the power supply quality of the active power distribution network is given.

The invention provides a true color-based massive point clouds dynamic display method, solving the defects of the prior art. The method comprises a first step of acquiring true color-based massive point cloud data, and performing optimization and reconstruction on the acquired point cloud data, wherein the optimization and reconstruction method comprises steps of first, performing orientation and parameter marking on the point cloud data by using a normal vector; then performing numerical reduction optimization on the massive point cloud data; and finally, forming a dynamic display marked data package of massive point clouds with true color; a second step of adjusting a data model according to access information of users, and displaying corresponding display information; and a third step of optimizing display data in the display process. In addition, the invention provides a true color-based massive point clouds dynamic display system. The system comprises an access information receiving module, a data processing module, a data storage module, and a display module. The feedback speed of the display image is faster than that in the prior art by 50% or more.