254 results about "High resolution imaging" patented technology

The invention relates to the technical field of crop disease and insect pest image recognition, and particularly discloses a crop disease and insect pest image recognition method based on a large model, and the method comprises the steps: obtaining a multi-angle leaf image through high-resolution imaging equipment under a controllable illumination condition, and obtaining a target image in a unified format; extracting scab texture complexity features in combination with a local binary pattern and a gray-level co-occurrence matrix algorithm, and performing multi-channel statistical analysis on RGB and HSV color spaces to generate color heterogeneity feature vectors; further fusing the two types of features into a composite disease feature vector, inputting the composite disease feature vector into a probability model constructed based on a support vector machine and a Monte Carlo Dropout mechanism, and outputting probability distribution and confidence score of disease and pest categories; and dynamically adjusting a model training strategy according to a confidence level, triggering a feedback mechanism for a low-confidence sample, generating a synthetic image by using a conditional generative adversarial network, and optimizing model parameters in combination with incremental learning to realize stable identification modeling of rare or complex disease types.

The invention discloses a large-view-field high-resolution imaging system based on polarization regulation and control, the large-view-field high-resolution imaging system comprises a metasurface system array and a camera along the direction of a light path, and the metasurface system array comprises a plurality of pairs of metasurface systems which are distributed in an array; each pair of metasurface systems comprises a first metasurface system and a second metasurface system; the first metasurface system is used for performing high-resolution imaging and large-view-field imaging on a first polarization light beam and a second polarization light beam of an incident light beam respectively; the second metasurface system is used for performing large-view-field imaging and high-resolution imaging on the first polarization-state light beam and the second polarization-state light beam respectively; the camera is used for acquiring and fusing images formed by different metasurface systems so as to capture a high-resolution central region of interest and surrounding environment information of a wide field of view. The system can efficiently realize higher imaging quality.

The invention discloses a terahertz continuous wave wind power blade defect imaging method based on an unmanned aerial vehicle platform, relates to the technical field of blade defect imaging, and solves the problems that in the prior art, when a crawling robot serves as a contact type mobile platform to detect a wind power blade, the process is tedious and time-consuming, and safety risks exist. According to the method, an efficient and flexible non-contact detection mode is provided, the unmanned aerial vehicle is adopted as an aerial autonomous bearing platform, contact dependence on the surface of the blade is overcome, rapid deployment, long-distance maneuvering and flexible arrival of detection equipment are achieved, and the detection operation efficiency and safety of the high-altitude and in-service wind power blade are greatly improved; the invention further provides a split type terahertz transmission imaging method capable of being integrated with an unmanned aerial vehicle platform, visual and high-resolution imaging of bubbles, layering and other defects in the blade is achieved by means of the penetrating characteristic of terahertz waves to a composite material, and the defect that in the prior art, the internal defect detection capacity is insufficient is overcome.

The invention discloses a scattered wave seismic acquisition and imaging method based on a full random observation system, which belongs to the technical field of seismic exploration and comprises a quasi-Monte Carlo random observation array design step, a scattered wave intelligent identification and enhancement step, a sparse wave field reconstruction step and a multi-target optimization imaging step. The limited equidistant property is ensured through the random observation array design based on a low-difference sequence, intelligent separation and enhancement of scattered waves are realized by using a physical constraint neural network, a sparse reconstruction problem is solved by using an alternating direction multiplier algorithm, a multi-target optimization imaging framework is constructed to realize high-resolution imaging, and high-resolution imaging is realized. The four core steps form a closed-loop cooperative system, sparse reconstruction quality evaluation feedback optimizes observation array design, imaging quality measurement feedback adjusts scattered wave identification parameters, and cooperative interaction is achieved.

The application discloses a kind of nnUNet zebra fish juvenile whole brain vascular system segmentation methods based on autonomous data set training, it is related to high-resolution imaging technology, image processing and medical image segmentation field, the method makes full use of zebra fish live transparency and fluorescent label advantage, obtains high-resolution whole brain three-dimensional vascular image data, and constructs high-quality segmentation truth value database by semi-automatic segmentation and artificial correction, training is carried out using nnU-Net deep learning model, realize the three-dimensional automatic segmentation of zebra fish brain vascular system signal.The application method significantly improves the degree of automation and precision of image segmentation, effectively solves the problems of low efficiency, high artificial dependence and poor repeatability of traditional brain vascular segmentation.The method is suitable for large-scale high-throughput data processing, can provide efficient, standardized image processing scheme for zebra fish brain vascular development mechanism and brain vascular disease model research, and has wide application prospect.

The invention relates to an aliasing image target recognition and positioning algorithm based on sub-view-field shape modulation coding, relates to the technical field of aliasing image target recognition and view field judgment and positioning, and solves the technical problem that the scale and view field of a detector cannot be considered when large-view-field and high-resolution imaging is realized under the condition of a limited detector in the prior art. The algorithm comprises the following steps: identifying a foreground target; tracking a target rotation state; and judging the relevance between the target motion trail and the light spot shape change trend and inversely solving the actual spatial position. According to the aliasing image target recognition and positioning algorithm based on sub-view-field shape modulation coding, space-based early warning and large-width detection are achieved through the advantages of low power consumption and low cost of a small target surface detector, and the bottleneck that large-view-field imaging of an infrared optical system is limited by the manufacturing process of an infrared detector is broken through. According to the invention, through continuous frame light spot morphological feature extraction and trajectory-shape double-domain correlation modeling, unique determination and high-precision positioning of a view field of an object space where a target is located are realized.

The invention discloses a tissue slice high-resolution mass spectrum imaging method and system based on multi-modal data fusion, and belongs to the technical field of mass spectrum imaging and biomedical detection. The method comprises the steps of multi-modal data acquisition, data preprocessing, feature extraction, multi-modal data fusion and high-resolution imaging reconstruction. High-resolution mass spectrum data and high-stability auxiliary modal data are synchronously collected, after preprocessing and feature extraction, feature weights are dynamically distributed and fused by using a fusion model based on an attention mechanism, and then a high-resolution and high-sensitivity imaging result is output through an imaging reconstruction model of a U-Net improved architecture. On the premise that the spatial resolution is not reduced and the sample is not damaged, the mass spectrum signal intensity is effectively enhanced, the low-abundance biomarker recognition capability is improved, the imaging efficiency is high, the adaptability is high, and the method is suitable for biomedical research and clinical diagnosis scenes.

The invention discloses a rockburst risk identification method based on a dynamic interference compensation algorithm and quasi-three-dimensional high-resolution imaging. The rockburst risk identification method comprises the following steps: separating construction noise and a rock mass fracture signal in real time by adopting a variational mode decomposition-particle swarm optimization algorithm; a high-frequency tunnel electromagnetic signal and a rock mass fracture signal are obtained, and an inversion imaging image is obtained through quasi-three-dimensional inversion of multi-band data fusion; and according to the inversion imaging image, the fracture density and the extension direction are extracted, and the trained LSTM model is used to carry out rockburst risk identification. Through the scheme, the method has the advantages of simple logic, accuracy, reliability and the like, and has very high practical value and popularization value in the technical field of tunnel construction safety monitoring.

The embodiment of the invention provides a method and device for detecting a mine water guide channel, electronic equipment, a storage medium and a program product. The method comprises the following steps: in response to acquired seismic shot gather data associated with a mine target area, separating a time domain diffracted wave signal from the seismic shot gather data; performing dip angle domain conversion on the time domain diffracted wave signal by using a preset conversion rule to obtain a dip angle domain diffracted wave field; wherein the dip angle domain diffracted wave travel time equation is involved in the dip angle domain diffracted wave field; based on the travel time equation, utilizing Taylor approximation to construct a diffracted wave target function; on the basis of the target function, diffracted wave event inversion operation is executed, and an optimal superposition path is obtained; and based on the dip angle domain diffracted wave field and the optimal superposition path, performing superposition operation, and generating a water guide channel imaging result of the mine target area. By utilizing the method disclosed by the embodiment of the invention, the speed sensitivity limitation of a traditional method can be broken through, and high-resolution imaging of a small-scale water guide structure is realized.

The application discloses a kind of multiscale unmanned aerial vehicle image monitoring crop growth methods and systems, belong to agricultural remote sensing and intelligent monitoring technical field.The method of the present application comprises: controlling unmanned aerial vehicle to collect target area low-resolution remote sensing image at first height;Based on first identification model, crop land boundary is extracted and divided into multiple grids;The health index of each grid is calculated, and the center point of the abnormal grid is located based on the statistical threshold value;Control unmanned aerial vehicle to descend to second height and fly to the top of abnormal grid to carry out leaf scale high-resolution imaging;High-resolution image is input into second identification model, and output fine diagnosis results such as water shortage, lack of fertilizer, disease and pest.The present application realizes the organic combination of large-scale rapid screening and local accurate diagnosis through two-level scale cooperative monitoring, greatly improves the efficiency and accuracy of crop growth monitoring, and is suitable for field crop automation, intelligent growth management.

The application discloses a kind of real synthetic aperture imaging methods for multichannel radar forward-looking imaging, first, the echo data of the region to be imaged is obtained, second, the data obtained is compressed in range direction pulse, then the data after pulse compression is respectively processed in synthetic aperture and real aperture, for synthetic aperture dimension, using BP algorithm is focused in azimuth direction, and the results of each channel are incoherently accumulated, to obtain left-right ambiguous image, for real aperture dimension, the imaging scene is divided into grid, constructs guide matrix, reconstructs target scattering coefficient to realize super-resolution imaging, finally, the results of two dimensions are multiplied, to obtain non-ambiguous and super-resolution result.The method of the application fully utilizes the advantages of high resolution obtained by platform motion synthetic aperture in squint region and high resolution obtained by azimuth real aperture super-resolution in forward-looking region, overcomes the problem of single-base radar forward-looking imaging ambiguity and low resolution, and realizes multichannel radar non-ambiguous forward-looking high-resolution imaging.

The utility model relates to the technical field of optical devices, in particular to a shutter assembly and a slit type large-format scanning camera, the shutter assembly comprises a film box, a slit scanning mechanism and a linear driving mechanism, and a photosensitive component is arranged in the film box; the gap scanning mechanism comprises a bearing part and a rigid insertion sheet; the bearing part is in guide fit with the film box; the rigid insertion sheet is inserted into the film box, two ends of the rigid insertion sheet are fixed on the bearing component, and a gap is formed in the rigid insertion sheet; the linear driving mechanism comprises a supporting part, a driving part and a transmission part, and the driving part is arranged on the supporting part; the transmission part is arranged on the supporting part and is in transmission fit with the driving part, and the transmission part is connected with the bearing part. According to the utility model, the driving part and the transmission part in the linear driving mechanism are matched to realize the rapid and slow linear motion of the bearing part, so as to drive the rigid insertion sheet to stably scan the photosensitive part and ensure that the light is irradiated on the photosensitive part in an accurate slit form, and the high-quality and high-resolution imaging effect can be obtained.

The invention discloses a high-resolution imaging method and system for the surface of the inner wall of a cavity hole of a complex workpiece. The imaging system extends into the workpiece cavity hole at a constant speed along the centroid axis direction of the workpiece cavity hole, and acquires images at a preset frame rate to obtain a plurality of frames of cavity hole inner wall images; extracting the plurality of frames of cavity hole inner wall images to obtain an annular scanning area of each frame of cavity hole inner wall image; expanding the annular scanning area in each frame of cavity hole inner wall image through coordinate mapping to obtain a rectangular expanded view of the annular scanning area in each frame of cavity hole inner wall image; and splicing the rectangular expanded images of the annular scanning areas in the cavity hole inner wall images according to an acquisition sequence to obtain a panoramic expanded image of the cavity hole inner wall of the workpiece. According to the invention, a high-resolution panoramic unfolded image of the inner wall surface can be obtained, and the method is suitable for visual detection of the inner wall surfaces of workpiece cavity holes with various complex section shapes.

The invention discloses a two-dimensional polycrystalline selenium nanosheet and a preparation method and application thereof.The nanosheet is prepared by processing selenium nanoparticles through a hot-pressing method, the nanosheet is structurally characterized in that triangular crystal phase selenium and orthorhombic crystal phase selenium coexist, and the orthorhombic crystal phase is concentrated in the center and rich in point defects; the nanosheet can generate a plurality of ultra-narrow linewidth photoluminescence peaks from visible light to near-infrared band at room temperature, and the minimum full width at half maximum can reach 387 + / -90 [mu] eV. According to the method, local phase change is induced through thermal stress under the limitation of the substrate in the hot pressing process, and controllable construction of a polycrystalline structure is achieved. The obtained polycrystalline selenium nanosheet can be used as a high-color-purity luminescent material, is used for preparing an ultra-narrow linewidth photoelectric emitter working at room temperature, and has a wide application prospect in the fields of quantum photonics, high-resolution imaging, spectral analysis and the like.

The invention relates to an athermalization optical system. The system comprises a protection window, a first lens, a second lens, a third lens, a fourth lens, a fifth lens, a sixth lens, a seventh lens, an eighth lens, a ninth lens, a tenth lens, an optical filter, a detector window and an image plane which are sequentially arranged in the light propagation direction and share the same optical axis. The first lens is a negative meniscus lens protruding towards the object side. The second lens is a biconcave lens; the third lens is a biconvex lens; the fourth lens is a positive meniscus lens protruding towards the object side. The fifth lens is a negative meniscus lens protruding towards the object side. The sixth lens is a biconvex lens; the seventh lens is a biconcave lens; the eighth lens is a biconvex lens; the ninth lens is a negative meniscus lens protruding towards the image space. The tenth lens is a biconvex lens; the surface of each lens is a spherical surface; the diaphragm is arranged on the front surface of the sixth lens. The optical system has the advantages of large field of view, high-resolution imaging, simple and reliable structure, high assembly efficiency and capability of being produced on a large scale.

This invention relates to the field of AR device technology, providing an AR optical lens and an AR device. The lens includes a first lens, a second lens, a third lens, a fourth lens, and a fifth lens arranged sequentially along the optical axis from the object side to the image side. The first lens has positive optical power, with a convex surface on the object side and a concave surface on the image side; the second lens has positive optical power, with a convex surface on the object side and a concave surface on the image side; the third lens has negative optical power, with both the object side and the image side being concave; the fourth lens has positive optical power, with a concave surface on the object side and a convex surface on the image side; and the fifth lens has negative optical power, with a concave surface on the object side and a convex surface on the image side. All lenses are aspherical lenses. This invention, through a positive-positive-negative-positive-negative optical power arrangement of lenses, can simultaneously correct various aberrations such as spherical aberration, field curvature, and distortion, effectively achieving a large field of view, low distortion, and high resolution imaging effect, enhancing the immersiveness and clarity of AR displays.

The present application relates to the field of optical imaging technology, and particularly relates to a full-depth-range high-lateral-resolution OCT imaging method, system and storage medium based on interference synthetic aperture. The OCT imaging method comprises sample positioning: moving the point spread function of the sample to a region close to 0 optical path; collecting three-dimensional original data; pre-processing the collected three-dimensional original data to obtain complex signals containing amplitude and phase information; performing three-dimensional Fourier transform on the scattering potential distribution based on a synthetic aperture algorithm to obtain frequency domain signals, correcting the nonlinearity of the spatial frequency by interpolation or frequency domain filtering before interpolation, and then performing inverse Fourier transform to reconstruct the spatial distribution of the scattering potential and obtain three-dimensional image data. The detail information of the defocus region is recovered, high-resolution imaging in the full depth range is ensured, and the inherent contradiction between lateral resolution and focal depth is broken through.

The invention relates to high resolution PET-CT imaging using PCCT and an advanced generative model. Systems and methods for generating a high resolution photon counting CT (PCCT) and PET image using a pair of high resolution PET images from the same patient. A machine learning network is trained on pairs of images from a patient. When the trained model is applied, new patient's PET and PCCT images may be used to generate high resolution PET images for medical diagnosis or further processing.

The application discloses a kind of synthetic aperture assisted multi-channel radar forward-looking learning imaging method, first, the echo data of the region to be imaged is acquired, the data obtained is compressed in distance direction pulse, then the echo data after pulse compression is imaged using the synthetic aperture assisted depth unfolding iterative shrinkage threshold algorithm ISTA network, i.e. in real aperture dimension, the imaging problem is converted into the estimation problem of target scattering coefficient, the target function is solved using the depth unfolding ISTA network, then the azimuth focusing is carried out using back projection BP algorithm in synthetic aperture dimension, then the synthetic aperture dimension result and the ISTA network result are fused to obtain the left-right unambiguous super-resolution imaging result.The method of the application overcomes the problem of left-right ambiguity and low resolution of single-base radar forward-looking imaging, realizes multi-channel radar forward-looking high-resolution imaging, and through depth learning, the parameter setting step is saved, the efficiency is improved, and the problem of signal-to-noise ratio sensitivity is overcome.

The application relates to a multi-aperture imaging space remote sensing target positioning optical system and a calibration method, and relates to the field of remote sensing and aerospace imaging optical instruments. The application solves the contradiction between the requirements of a large field of view and high resolution imaging of a traditional single-aperture optical imaging system, and realizes accurate positioning of a target to meet the intelligent requirements of a multi-aperture optical imaging system. The multi-aperture imaging space remote sensing target positioning sub-aperture imaging optical system comprises an electromagnetic vibration mirror, a beam-reducing telescope group, a fast reflection mirror and a rear focusing mirror group. The beam-reducing telescope group and the rear focusing mirror group are connected through the fast reflection mirror, and the light beam is connected with an imaging branch through the electromagnetic vibration mirror. After the imaging light beam passes through the telescope system, the imaging light beam is reflected by the fast reflection mirror and focused on a detector to form an image. The application is also suitable for a mobile platform for fast positioning and high-precision capturing of a dynamic target in the field of industrial precision machining and space remote sensing.

The invention discloses a rare earth homologous dual-emission high-resolution deep imaging method based on deep learning enhancement. A plurality of long-life intermediate states of lanthanide upconversion nanoparticles (UCNPs) are utilized, a single 980nm pumping source is used for exciting Tm < 3 + > / Yb < 3 + > co-doped UCNPs, and two-photon fluorescence with higher penetrability and four-photon fluorescence with higher resolution are induced at the same time. By combining a dual-mechanism CycleGAN artificial neural network based on antagonism training and cyclic consistency constraint, cross-domain mapping between two fluorescence signals is established, and the advantages of two fluorescence imaging are cooperatively utilized, so that deep penetration and high-resolution imaging are realized. According to the invention, in a self-established wide-field microscopic imaging system, the resolution of 209nm of a single particle in a 808nm fluorescence channel can be realized, and the signal-to-background ratio is doubled. According to the invention, the technical bottleneck that the resolution and the penetration depth of a traditional multi-photon microscope in deep tissue imaging are mutually restricted is effectively solved.

The application discloses a visible light wide-band long-focus lens, a camera module and a terminal device. The visible light wide-band long-focus lens comprises a first lens, a second lens, a third lens, a fourth lens, a fifth lens and a sixth lens which are sequentially arranged along an optical axis from an object plane to an image plane; one of the first lens, the second lens, the third lens, the fourth lens, the fifth lens and the sixth lens is an ultra-surface lens, and the rest lenses are all spherical surface lenses; the application combines the five spherical surface lenses with the one ultra-surface lens, and cooperates the lens materials and optical powers, so that the total optical length of the lens is effectively compressed, and the miniaturization and light weight design is realized. Meanwhile, the relationship among the relative illumination RI , the effective area size of the ultra-surface lens D M and the optical distortion value D 0 is optimized, so that the long-focus lens has the ability of high resolution and low aberration, and especially realizes the advantages of high-resolution imaging in the visible light wide-band range.

The utility model relates to the bearing ring detection field, and discloses a bearing ring high precision detection device comprising a fixed rack and a rotating rack, the periphery of the rotating rack is provided with the fixed rack, the bottom of the rotating rack is provided with a pedestal supported on the ground, and a steering motor is fixed in the pedestal; an output shaft of the steering motor is fixedly connected to a placement table upwards, a bearing ring to-be-detected piece is placed at the top of the placement table, a vertical frame standing on the ground is arranged at the front end of the fixing frame, and a lifting motor is fixedly connected to the top end in the vertical frame. According to the high-precision detection equipment for the bearing ring, the rotating stand is arranged, the CCD detection head adopts a high-resolution imaging technology, the surface of a to-be-detected part of the bearing ring is shot frame by frame in the rotating process, image data are processed in real time by operating a display, and high-precision and high-efficiency outer wall full-coverage detection is realized by combining automatic rotation and lifting adjustment; and the problem of false detection rate caused by artificial misjudgment is solved.

The application discloses a multi-target particle swarm optimization-based multi-base SAR space configuration design method, which comprises the following steps: firstly, setting multi-base SAR space configuration design parameters, modeling a multi-base SAR echo model, and then performing multi-base SAR imaging wave number spectrum analysis; secondly, modeling a space configuration optimization design problem, inputting space configuration optimization design problem system parameters and configuration parameters, initializing MOPSO, then updating the speed and position of the particle swarm, and finally outputting the optimized configuration through iterative updating. The method of the application converts the space configuration design problem into a constrained multi-target optimization problem, introduces a multi-target particle swarm optimization algorithm for solving, realizes high-resolution imaging through the optimized space configuration, breaks through the strict limitation of the multi-base SAR space configuration, and can complete the optimization design of the relative positions and flight speed directions of multiple radar platforms under certain time and system resource conditions, so that higher-resolution images can be obtained within a certain observation time.

The invention relates to the technical field of hyperspectral remote sensing spectral analysis, in particular to a full-spectrum splicing high-resolution imaging system and method for a hyperspectral analyzer, and the method comprises the steps: determining a slit switching sequence through an acquisition module; the dynamic collimation module feeds back an aberration result; the adaptive dispersion module carries out wavelength calibration; the high-precision imaging module predicts imaging mirror parameters; the real-time compensation module adopts a Kalman filtering algorithm to predict the defocus compensation amount and executes nanoscale displacement compensation through a piezoelectric ceramic driver; the intelligent splicing module adopts an SIFT feature matching algorithm, a generative adversarial network and a reinforcement learning algorithm to realize image registration and fusion; the cooperative control module generates control signals through Monte Carlo simulation and a Bayesian optimization algorithm to coordinate all the modules. According to the invention, the problems of insufficient spectral resolution, difficulty in data splicing and low real-time measurement efficiency caused by fixed hardware parameters in a wide-spectrum spectral imaging system are solved, and full-spectrum high-resolution imaging is realized.

The present invention provides a vision system camera having a multi-core processor, high speed and high resolution imager, field of view extender, auto focus lens, and pre-processor connected to the imager for pre-processing image data, and a coordinated method of operation, which provides highly desirable acquisition and processing speed, as well as image clarity, in a wide range of applications. The mechanism is effective for scanning objects requiring a wide field of view, varying in size, and moving relatively rapidly with respect to the system's field of view. The vision system provides a physical package having a variety of physical interconnect options to support a variety of options and control functions. The package is effective in dissipating heat generated internally by arranging components to optimize heat exchange with the surrounding environment, and including heat dissipation structures to facilitate such heat exchange (e.g. fins). The system also allows for a variety of multi-core process optimization and load balancing of image processing and system operation (e.g. automatic adjustment of tasks).

The invention discloses a microseism monitoring and positioning method based on adaptive probability imaging. Comprising the following steps: S1, arranging a detector and collecting data; s2, picking up arrival time and calculating a signal-to-noise ratio; s3, constructing an EDT residual error; s4, constructing an adaptive probability density function; s5, positioning imaging in a product form; s6, searching an optimal seismic source position; and S7, removing abnormal data. The beneficial effects of the invention are that the method achieves the high-resolution imaging of the position of the seismic source and the effective suppression of an abnormal value.

The invention discloses a large-view-field high-resolution microscopic module which comprises a supporting plate, an imaging assembly located at the top of the supporting plate, a dual-mode imaging switching assembly and a light source output assembly which are located at the bottom of the supporting plate, and an observation module located below the dual-mode imaging switching assembly. The dual-mode imaging switching assembly comprises an adjusting bin, a bright field reflection module and a fluorescence excitation module, wherein the bright field reflection module and the fluorescence excitation module are movably arranged in the adjusting bin. The adjusting bin is provided with an emergent hole communicated with the imaging assembly, a light hole communicated with the light source output assembly and an observation hole communicated with the observation module. According to the arrangement, the bright field reflection module and the fluorescence excitation module are moved to the light path communication position when needed, so that switching of imaging modes can be achieved, the switching structure is simple and easy to operate, and the number of imaging channels can be effectively guaranteed; and the clear aperture of the switching mechanism can be flexibly configured according to the pupil diameter of the objective lens, so that the effects of large view field and high-resolution imaging are achieved, and the application scene is wider.

The present application relates to a kind of protein and its application in intestinal flora magnetic resonance imaging positioning and tracking.The amino acid sequence of the protein includes the sequence shown in SEQ ID NO.1.The present application designs specific protein, the protein can be combined with endogenous manganese ion, and effectively enhance MRI signal, express in intestinal flora, can be used endogenous manganese ion to carry out magnetic resonance imaging, realize high-resolution positioning and dynamic tracking of intestinal flora, can avoid using exogenous contrast agent, no side effect or immune response, and can be non-invasive, real-time dynamic, high-resolution imaging, provide the spatial distribution and dynamic change information of intestinal flora.

The present application relates to the technical field of industrial vision detection and intelligent manufacturing, and in particular provides a papermaking wood grading evaluation method based on 3D vision and high-resolution imaging fusion. The method comprises raw material feeding and pre-screening, and collecting front and back multi-modal information to realize heterogeneous data archiving, establish an initial digital archive of the target physical form; camera alignment and foreground segmentation are performed, and material categories and associated metadata are identified to obtain offline grading evaluation. Through hardware synchronization and algorithm cooperation, the method realizes automatic collection of front and back of wood, calculation of three-dimensional geometric parameters, material classification and grading evaluation, significantly improving detection accuracy, reviewability and automation level.