73 results about "Micrograph" patented technology

The invention provides an ore recognition method and system based on a large model algorithm, and is applied to the technical field of computer vision and data processing, and the method comprises the steps: obtaining an ore microscopic image, and generating a feature point location candidate set through a convolutional neural network model; calculating a spectral value and a morphological parameter of each feature point location to determine a multi-dimensional data point; clustering the multi-dimensional data points to obtain a feature point cluster; and when the spatial distance between the adjacent feature point position clusters is smaller than a first preset threshold value and the spectral similarity is higher than a second preset threshold value, combining the adjacent feature point position clusters into the same mineral region. The segmentation precision and the type identification accuracy of the complex symbiotic mineral area can be obviously improved.

The embodiment of the invention relates to a processing method and device for generating an electron microscope graph big data set. The method comprises the following steps: constructing a first data set; taking the first-class visual semantic segmentation large model as a first segmentation model, and taking the SDXL model as a first generation model; performing fine adjustment on the first segmentation model according to the first data set, and then performing fine adjustment on the first generation model according to the first data set and the first segmentation model; constructing a first simulation semantic segmentation image library; and performing simulation electron microscope graph generation processing by a first generation model according to the first simulation semantic segmentation graph library, forming a second data record by each first simulation electron microscope graph and the corresponding first simulation semantic segmentation graph, and forming an electron microscope graph big data set by all the obtained second data records. According to the invention, a large number of electron micrographs can be automatically generated without the help of any manpower or external resources, and the data preparation difficulty of the electron micrograph big data set is reduced.

An infectious disease infection prediction method and device based on macrograph-micrograph fusion, and a storage medium. The method comprises: acquiring macrographs of a plurality of first areas and micrographs of second areas in a certain set time period; respectively inputting the macrographs and the micrographs into a first graph convolutional neural network and a second graph convolutional neural network to respectively obtain a first hidden layer vector and a second hidden layer vector, and fusing the first hidden layer vector and the second hidden layer vector to obtain fused hidden layer information of each first area; performing temporal calculation on the fused hidden layer information to obtain temporal hidden layer information of each first area, and separately inputting the temporal hidden layer information into two prediction networks to obtain two prediction results; and performing fusion calculation on the two prediction results to obtain a final infectious disease prediction result for each first area.

To provide a method, device, and program for identifying a type of plating of an automobile steel plate for identifying a type of plating applied onto a steel plate to be used for a vehicle body configuration component of an automobile body.SOLUTION: A method for identifying a type of plating of an automobile body is a method for identifying a type of plating applied onto a steel plate to be used for a vehicle body configuration component of the automobile body. The method comprises: a steel plate cross-section gray scale image acquisition process S1 of sampling a steel plate from the vehicle body configuration component so as to manufacture a test piece including the steel plate, and imaging an optical microscopic photograph of the steel plate cross-section in the manufactured test piece so as to acquire a gray scale image; a gray scale gradation histogram generation process S3 of generating a histogram of a frequency of a gray scale gradation in the acquired gray scale image; and a plating type identification process S5 of identifying a type of plating applied onto the steel plate based on a distribution form of the generated histogram.SELECTED DRAWING: Figure 1

An infectious disease infection prediction method, an apparatus, and a storage medium based on macro-micrograph fusion are provided. The method includes: acquiring macrographs of a plurality of first regions and micrographs of second regions within a set period; inputting the macroscopic graphs and the microscopic graphs into two graph convolutional neural networks to obtain two hidden layer vectors respectively, and fusing the two hidden layer vectors to obtain fusion hidden layer information of the first regions; performing a time sequence calculation of the fusion hidden layer information to obtain time sequence hidden layer information of the first regions; inputting the time series hidden layer information into two prediction networks to obtain two prediction results, respectively, and performing fusion calculation of the two prediction results to obtain a final prediction result of infectious diseases in the first regions.

To provide: an aqueous dispersion of fine inorganic powder that exhibits excellent dispersibility in an aqueous medium and has high dispersion stability; and a cosmetic preparation containing the aqueous dispersion, which is highly stable and excellent in transparency, usability (non-stickiness), and water resistance.SOLUTION: An aqueous dispersion contains: (a) 10-70 mass% of hydrophobized titanium oxide fine particles which have a number average primary particle diameter of 8-200 nm as determined by an image analysis method of a transmission electron micrograph and are obtained by hydrophobizing titanium oxide particles with silicone; (b) 1.0-30 mass% of an aqueous component which has two or more alcoholic hydroxyl groups; (c) 1.0-20 mass% of a polyglycerol-modified silicone which can be dissolved in the component (b); and (d) 8-82 mass% of water.SELECTED DRAWING: None

The present application relates to microlens three-dimensional imaging technical field, specifically relates to micrograph array method and three-dimensional dynamic imaging material with micrograph, aims at solving the problem that microlens three-dimensional imaging cannot simultaneously meet fixed visual angle stable imaging and variable visual angle dynamic response.The technical scheme main points are: including transparent substrate layer;Micrograph structure layer;Microlens structure layer, microlens structure layer is located on the side of transparent substrate layer away from micrograph structure layer;Vacuum coating layer, vacuum coating layer is arranged on the surface of microlens structure layer, microlens structure layer is matched with micrograph structure layer, so that three-dimensional dynamic imaging material presents integrated micrograph three-dimensional dynamic stereoscopic image that changes with observation angle in the visual angle range, micrograph structure of different visual angle frame rate is fused according to the viewing angle segmentation, and a kind of three-dimensional dynamic imaging film material is made, and the image gradually changes when micrograph is seen through vacuum coating layer reflection formed when viewing visual angle or deflecting material changes.

Provided herein is a method of imaging and analyzing plant microspores. The method comprises obtaining one or more two-dimensional micrographs of a microspore population, wherein the microspore population has not been labeled; sending the one or more two-dimensional micrographs to an image processing system; segmenting, via the image processing system, the one or more two-dimensional micrographs to distinguish individual microspores, thereby creating a segmented population of microspores; obtaining one or more z-stacks of the population of segmented microspores or the population of microspores to be segmented; and using one or more of pixel intensity information and intensity signal processing within the one or more z-stacks of segmented cells to find nuclear edges and nuclear geometry and determining whether cells are uninucleate or binucleate based on the nuclear edges and nuclear geometry. Also provided herein is a method of imaging and analyzing plant microspores comprising determining microspore viability.

Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for determining the 3D structure of a type of particle. The system obtains one or more two-dimensional (2D) micrograph images of the sample, and performs a process for generating a set of representative 2D projections of the type of particle from the 2D micrograph images. The system obtains metadata for each class representation image, and selects, using the metadata, a set of representative 2D projections from the class representation images. The system reconstructs a 3D image of the type of particle using the set of representative 2D projections, and outputs the 3D image of the type of particle

The invention discloses a digital characterization method of a hypoeutectic aluminum-silicon alloy and a related device, and the method comprises the steps: obtaining a metallographic structure microphotograph of the hypoeutectic aluminum-silicon alloy, carrying out the preprocessing of the metallographic structure microphotograph, and obtaining a target metallographic structure microphotograph; the target metallographic structure microphotograph is transmitted to a preset eutectic aluminum-silicon extraction model, an eutectic silicon mask is obtained, and the eutectic silicon mask and the target metallographic structure microphotograph are the same in size; determining a silicon segregation region based on the eutectic silicon mask; and determining a dendritic crystal diagram based on the eutectic silicon mask, and calculating secondary dendritic crystal spacing and / or microscopic grain size based on the dendritic crystal diagram. According to the process, the eutectic silicon mask is obtained based on the preset eutectic aluminum-silicon extraction model, the silicon segregation area, the secondary dendritic crystal spacing and the microscopic grain size can be determined based on the eutectic aluminum-silicon mask, all processes are automatically completed, manual operation is not needed any more, and the efficiency is high. The problems that in the prior art, artificial experience is high in subjectivity, analysis time is long, local statistics is limited, and precision is not high are solved.

The invention discloses a Fourier lamination imaging phase compensation method for a full-view-field vignetting micrograph. In the Fourier laminated imaging technology, the local information of the reconstructed phase is lost due to the influence of the vignetting effect. The method comprises the following steps of: firstly, simulating a vignetting effect of phase curvature change caused by illumination delay in a light wave propagation process by introducing a phase factor with adjustable parameters; sequentially performing phase recovery on the images by using an alternating projection algorithm; a phase of a reconstructed high-resolution image is obtained through iterative convergence in a frequency domain, phase compensation is performed on the reconstructed phase by using an accurate conjugate phase, and finally a reconstructed image including compensated phase information is obtained. Therefore, the Fourier lamination imaging phase compensation method for the full-view-field vignetting micrograph can eliminate the problem that the phase of the image cannot be correctly reconstructed due to introduction of the phase curvature, and further improves the image phase reconstruction quality.

The utility model provides a kind of microscope external optical fiber lighting device, it is related to microscope lighting device technical field, including optical fiber, the one end of optical fiber corresponds with light source, and the other end extends to the light path entrance of the illumination system of microscope;The illumination system is sequentially provided with variable aperture diaphragm, condensing system and objective along light path propagation direction, and the aperture size of variable aperture diaphragm is changed to control the numerical aperture of illumination;The light emitted by light source is transmitted to variable aperture diaphragm by optical fiber, and clear micrograph is formed by condensing system, objective.The utility model has the beneficial effect of not only breaking through the constraint of traditional built-in illumination in physical space, and heat source can be completely isolated in microscope outside, avoid the occupation of light source to microscope internal space and the influence of cooling fan vibration on microscopic observation, in addition, different microscopes can be matched by different light sources, with flexible adaptive expansibility, can be widely applied to various microscopic observation systems.

The present invention belongs to the field of composite material detection technology, and specifically discloses a method and system for quantitatively evaluating the orientation of composite material filling particles, which includes S1, obtaining a cross-sectional micrograph of the composite material to be tested and converting it into a grayscale image; S2, processing the grayscale image to obtain a binary image; S3, traversing all pixel blocks in the binary image, obtaining the image longitudinal continuity SSV and the image transverse continuity SSH, and then obtaining the vertical orientation ORI; S4, rotating the binary image multiple times according to a preset angle, repeating steps S2 and S3 each time the image is rotated, and obtaining a curve of the vertical orientation varying with the rotation angle, wherein the maximum value of the vertical orientation in the curve and its corresponding rotation angle are the image orientation and orientation angle. The present invention does not require other complex equipment and instruments, and is not affected by the crystal structure of the filler particles; at the same time, the present invention performs full-image processing on the binary information, and also has excellent evaluation effects on complex filler particle information.

The invention relates to a method for generating a three-dimensional structure of a porous material through image data processing and application of the method, and belongs to intersection of three-dimensional reconstruction, deep learning and material characterization. The problems that when the prior art is directly used for constructing the three-dimensional structure of the material, computing resource consumption is large, functions are split, simulation adaptability is poor, data dependence is high, and angle features are limited are solved. The invention relates to a method for generating a porous material three-dimensional structure through image data processing, which comprises the following steps of: 1, screening two-dimensional images to obtain images conforming to a signal-to-noise ratio and a contrast ratio as input microscopic image samples, and preprocessing the input microscopic images to generate a training sample set; 2, constructing a model of the algorithm; 3, training models, including discriminator model training and generator model training; and 4, inputting a sample image into the trained model, and obtaining a corresponding three-dimensional voxel structure based on the output three-dimensional probability voxel structure.

The application discloses a method for judging the sensitivity of a titanium alloy to sustained fatigue, which comprises the following steps: step (1): a mathematical model formula y=kx+b is simulated by using titanium alloy forging samples with different feather organization contents and a sustained fatigue sensitivity coefficient; in the formula, x represents the feather organization content, and y represents the sustained fatigue sensitivity coefficient; and step (2): the feather organization content of a titanium alloy forging sample to be detected is substituted into the mathematical model formula to obtain the result; the feather organization is a flaky cluster alpha phase in a net basket organization observed by a metallographic microscope, and the content of the feather organization is a ratio of an area of the feather organization to a total area of the net basket organization in a metallographic micrograph taken. The judging method can quantitatively judge the sustained fatigue sensitivity coefficient of the titanium alloy forging sample according to the microstructure characteristics of the titanium alloy forging sample in engineering, and the sustained fatigue value of the material does not need to be measured when mass-produced forgings or a process window is adjusted.

Provided is a dispersion having excellent dispersibility, especially dispersibility in aqueous media, water resistance, and feel on use (absence of stickiness) that contains components (a)-(d): (a) 10-85 mass% of a hydrophobized inorganic powder having a number-average primary particle size by image analysis of a transmission electron micrograph of more than 200 nm and equal to or less than 700 nm, (b) 1-80 mass% of an aqueous component having two or more alcoholic hydroxyl groups, (c) 1-20 mass% of a polyglycerol-modified silicone that is soluble in component (b), and (d) 0-2 mass% of a polyglycerol-modified silicone that is insoluble in component (b), where the ratio of the content of component (d) to the content of component (c) represented by (d) / (c) is 0.1 or less.

A method of automated control of a microscope in cryogenic electron microscopy (cryo-EM), wherein the microscope is configured to collect high-magnification micrographs of particles suspended in vitreous ice. Such particles are found in grid squares, and a square contains holes from which high-magnification micrographs are imaged. The method is carried out during an active data collection session, leveraging a pipeline that comprises a set of models. The pipeline evaluates a set of collection locations to determine whether to continue collection at a current grid / square or instead at a new grid / square. The evaluation is based on a set of one or more quality scores derived from one or more pretrained models and machine learning-based active learning. Based on the determination, control information is provided to automatically control the microscope to move to a next target for data collection.

The present invention belongs to the field of cartridge case manufacturing, specifically to a method for predicting cartridge case material properties from SEM images based on explicit Fast Fourier Transform (FFT). The method comprises the following steps: S1, sampling the cartridge case material before stamping to produce an SEM sample; S2, taking a micrograph of the sample and performing electron backscatter diffraction analysis to obtain an SEM image and EBSD data; S3, creating a three-dimensional voxel map of a representative volume unit from the SEM image, and using the EBSD data to generate Euler angle information for each three-dimensional pixel; S4, calculating stress and strain data for the three-dimensional voxel map of the representative volume unit using an explicit Fast Fourier Transform (FFT) method; and S5, using a tensor sparse symbolic regression method to learn the stress and strain data generated in step S4 to generate a constitutive model for the cartridge case material. The present invention can accurately predict the large deformation plastic mechanical properties of the cartridge case material from the results of the microstructural analysis of the cartridge case material.

Provided are a representative micrograph determining method, a representative micrograph determining device, an imaging device, and a program that can objectively and efficiently determine a representative micrograph from a plurality of micrographs of a metal material. The representative micrograph determining method includes: an input process of acquiring a plurality of micrographs taken at two or more magnifications for two or more fields of view of a metal material (S11); a phase classification process of classifying phases in the plurality of micrographs (S12); a quantitative value calculation process of calculating quantitative values of the phases classified (S13); a magnification determination process of determining a representative magnification based on the quantitative values (S14); and an output process of outputting the representative magnification (S17).

The invention discloses a patterned wafer microstructure data acquisition system in a bright field environment and a data set construction method. The system comprises an adjustable light source assembly, a microscope imaging assembly and a three-axis electric displacement platform, the data set construction comprises the following steps: fixing a patterned wafer sample on a three-axis electric displacement platform, and setting illumination brightness through an adjustable light source assembly to obtain uniform bright field illumination; the three-axis electric displacement platform is controlled to move along a preset path, automatic focusing scanning in the Z-axis direction is executed at each point position, and an optimal focal plane image is generated; the collected images are classified after being cut and preprocessed, and normal samples and abnormal samples are distinguished; for the abnormal sample, generating a defect mask file through interactive labeling; and integrating images and masks to form a structured data set which can be directly used for algorithm research. According to the method, microscopic images with high depth of field and high contrast can be obtained, and a high-quality anomaly detection data set directly used for deep learning model training is constructed.

The embodiment of the application relates to a kind of processing method and device for optimizing electron micrograph quality, the method comprises: one complete model pre-training DDPM model is recorded as first pre-training model;And by the way of fusing multiple LoRA adapters on first pre-training model, obtain first fusion model;Collect multiple spherical aberration electron micrograph to form corresponding first training atlas;The parameter set L of first fusion model is fine-tuned based on first training atlas;After fine-tuning, corresponding electron micrograph quality optimization processing is carried out to any ordinary transmission electron micrograph based on the second denoising autoencoder of first fusion model, and corresponding optimized electron micrograph is obtained.Through the application, the image quality of ordinary transmission electron micrograph can be optimized to reach the quality level of spherical aberration electron micrograph, and the model fine-tuning efficiency can be improved, and the model use cost is reduced.

A system for identifying microbial agents such as virus particles in a sample. The system includes at least one processing unit for identifying in an electron micrograph obtained from the sample a darker region and identifying virus particles within the darker region. The system can optionally include an electron microscope, a sample collector and sample treatment chamber.

The application discloses a kind of over-fire cable protection multi-material path micrograph generation methods based on Mamba, it is related to bridge cable protection material microstructure intelligent characterization field after fire.The method obtains the micrograph of different materials in cable protection system under different over-fire temperatures and different electron microscope magnifications, and constructs material micrograph sample library;Classify, differentially pretreat and conditionally label material micrograph, form conditional sample set;Construct micro-morphology generation model based on Mamba, and use latent space condition generation training strategy and multi-path parameter optimization method to train;The micro-morphology generation model that completes verification is encapsulated as lightweight plug-in, and target micrograph generation and output are realized.The application can realize the controllable generation of multi-material micrograph under small sample condition, and improve the characterization ability of material specific micro-morphology feature.

The invention provides a semiconductor defect detection method and device based on a microscopic atlas, and the method comprises the steps: selecting a spectrum band of infrared multi-spectrum-band microscopic imaging according to the type of a detected semiconductor material, carrying out the scanning imaging of a sample in a first preset view field and a first preset resolution ratio through an electric objective table, and splicing the scanning images into a complete microscopic image; analyzing the complete microscopic image, and positioning a suspected pollutant defect micro-area; performing infrared multi-spectrum microscopic imaging on the suspected pollutant defect micro-area in a second predetermined view field and a second predetermined resolution, identifying the defect type through an image processing algorithm, and if the suspected pollutant defect micro-area is determined to be a pollutant defect micro-area, switching to an infrared wide-spectrum microscopic spectrum measurement light path; fourier transform is carried out on the infrared spectrum light source, spectrum detection is carried out on the pollutant defect micro-area according to the Fourier transform result, collected spectrum data is compared with data in a preset database, and pollutant components and distribution are determined. The method provides guarantee for semiconductor quality control.

The present application relates to the technical field of agricultural product traceability, and discloses a kind of agricultural product pre-sale traceability method and system based on plant micrograph features, and macro image is collected during pre-sale period, and biological intrinsic coordinate system is established by extracting natural intersection node, and high-precision microscope camera is driven to collect reference micrograph, and reference micrograph is converted into gray scale scalar field function, and reference topological persistent graph is generated by extracting topological generator, and after coding, it is bound with pre-sale order in traceability cloud database by combining digital signature, and during review period, natural intersection node is extracted again to reconstruct coordinate system and calculate growth expansion coefficient to compensate deformation, and real-time topological persistent graph is calculated to construct cost objective function by extracting topological persistent graph, and according to space negative gradient closed loop servo micro-motion scanning and locking best deformation alignment point, verification pass signal is output under the condition that minimum value topological distance is lower than legal homology threshold and tamper-proofing check passes, and the present application realizes traceless right confirmation of living agricultural product features.

The invention belongs to the technical field of computer image processing, and relates to a metal material phase content analysis method and system, a storage medium and equipment, and the method comprises the following steps: collecting a color metallographic micrograph of a sample of a metal material, and constructing a data set of a metal material microstructure by using the color metallographic micrograph; using a label labeling tool to label the data set of the microscopic structure of the metal material; the basic operation module is used for constructing a metal material phase content analysis model based on an environment and an interface provided by a deep learning framework; constructing a model based on an improved U-shaped convolution / self-attention codec algorithm; training a model based on an improved U-shaped convolution / self-attention codec algorithm by using a data set marked by a metal material microstructure; and calculating the phase content of the metal material. The method solves the problem that a traditional image processing method is not easy to analyze the phase content formed by a complex structure.

The invention discloses a marking method and system for a compact sandstone microscopic image, and the method comprises the steps: carrying out the edge enhancement of particles in the compact sandstone microscopic image through an image processing technology, and obtaining a first image; the sandstone microscopic image segmentation model is used to carry out particle pre-labeling processing on the first image to obtain a second image, and the second image comprises at least one piece of editable labeling information formed according to the particle identification result; and modifying the particle recognition result of the second image according to the editable annotation information. According to the method, the labeling efficiency can be remarkably improved, and the labeling fineness and accuracy are improved.

The present invention discloses a holographic microscopic measurement method and device, which relates to the field of optical imaging and digital holographic technology. It is used to solve the problems that the existing digital holographic measurement method has a single detection mode, two-dimensional and three-dimensional detection cannot be performed simultaneously, and the existing multi-mode detection device requires time-sharing or multiple detectors for measurement, resulting in low measurement efficiency, poor data synchronization and high system complexity. It includes: a first rectangular aperture, which is used to shape the first transmitted light so that the first transmitted light forms a rectangular beam; a second splitting part, which is used to divide the first transmitted light into an object light and a reference light with a spacing; a second rectangular aperture, which is used to intercept the object light and the reference light to obtain a non-overlapping part of the reference light, and an overlapping part where a part of the object light and a part of the reference light overlap; an image detector, which is used to collect an off-axis hologram formed by the overlapping part and a micrograph formed by the non-overlapping part of the reference light.

The present application relates to the field of material science and engineering, in particular to a kind of porous material pore structure fast identification and three-dimensional model generation method.The present application is first to the two-dimensional micrograph of porous medium phase decoupling and feature extraction, obtains topological parameter set;Then through parameter space mapping establishes statistical feature matching model;Then generate geometric topological element in the feature space that satisfies the condition;Finally, the final continuous phase space domain is constructed using spatial domain topological mapping algorithm, for the digital reconstruction and performance simulation of porous material structure.The present application can effectively realize the identification and three-dimensional model construction of porous material pore structure, and the advantages of the model construction of the present application are verified through numerical simulation, which provides strong technical support for the research and application of porous materials.