532 results about "Rapid acquisition" patented technology

The invention discloses an expressway air-ground integrated intelligent tour inspection system, and relates to the technical field of expressway tour inspection. The inspection management platform is in communication connection with a data acquisition module, an environment perception analysis module, a target detection module, a disease target classification module, a pavement disease dynamic identification module and an inspection early warning management module, and the data acquisition module is used for collecting and preprocessing various inspection data required by highway inspection. Through cooperative work of air patrol of the unmanned aerial vehicle and the ground sensor, large-area patrol data can be rapidly obtained, all-directional and real-time monitoring of the expressway is achieved, the patrol efficiency is remarkably improved, a large-area patrol task can be completed in a short time, potential road diseases can be found in time, and the safety of the expressway is improved. Timely and accurate information support is provided for road maintenance and management departments, and safe and smooth operation of the expressway is guaranteed.

The invention relates to a geological mineral exploration data extraction method which comprises the following steps: S1, data acquisition: acquiring multi-source geological data through scientific drilling, remote sensing images and a geological radar; according to the method, through scientific drilling, remote sensing image and geological radar multi-source data collection, in combination with data preprocessing, feature extraction and three-dimensional model construction, massive geological data can be rapidly obtained and processed, and accurate positioning of mineral resources is achieved; the remote sensing image is combined to identify surface mineralization abnormity, the problem of surface and deep data separation in a traditional exploration method is effectively solved, meanwhile, the data preprocessing module ensures consistency and high-precision fusion of data from different sources through cleaning, format unification and geographical registration, and the data preprocessing module analyzes abundance and distribution rules of main metallogenic elements to obtain the data of different sources. And identifying combinations of elements closely related to mineralization.

The invention belongs to the technical field of novel fluorescent materials, and particularly discloses application of a mechanical color change pyrenyl derivative in latent fingerprint fluorescence imaging and extraction. The mechanical color-changing pyrenyl derivative can be selectively combined with fingerprint residual substances under the excitation of ultraviolet light through the unique fluorescence response characteristic, so that potential fingerprints form high-contrast fluorescence imaging on smooth or rough surfaces (such as glass, metal, plastic and the like), and the mechanical color-changing pyrenyl derivative is compatible with conventional camera equipment to realize rapid acquisition. The compound design is based on a modular synthesis route, and has the advantages of simple and convenient synthesis process, controllable raw material cost, high reaction yield and the like. The product has excellent thermal stability and chemical stability, can be stored at normal temperature and does not need special treatment, and the practical application threshold is greatly reduced. Compared with a traditional fingerprint developing technology, the method has remarkable breakthroughs in the aspects of sensitivity, substrate adaptability and operation convenience, and an efficient, economical and environment-friendly novel solution is provided for the fields of criminal investigation, forensic identification and the like.

The invention discloses a speed measurement method based on single-frame multiple exposure, and belongs to the field of hypersonic velocity field measurement. The implementation method comprises the following steps: recording equal time interval change of molecular marking in a flow field along with movement of the flow field through single-frame multi-time exposure imaging of an image enhancement camera, and realizing continuous and rapid acquisition of speed information within a short time after single-time marking. The morphological position after the time interval is determined according to the molecular marker, and the velocity field with spatial resolution in the flow field is extracted by mapping the marker before and after displacement, so that the velocity measurement precision is improved. Compared with other two-dimensional velocity field acquisition methods based on femtosecond laser molecular marker tracing velocity measurement, the method provided by the invention does not need a complex focusing lens combination, can obtain spatial positions of molecular markers at different moments only through isochronous continuous triggering exposure of a camera, thereby obtaining velocity flow field displacement information. And corresponding acceleration information can be further deduced according to the obtained velocity field. The method is especially suitable for hypersonic velocity field measurement.

Disclosed in the present invention is a photometric stereo-based device for rapidly detecting surface features of an object, capable of rapidly acquiring a plurality of images meeting the requirements of a photometric stereo algorithm. The device comprises a light emitting assembly, an acquisition assembly located above the light emitting assembly, and a data processing module; the acquisition assembly comprises a light path system and a camera group; the light path system comprises: a beam splitting prism group used for splitting reflected light from the surface of an object into a plurality of beams of light and respectively outputting the plurality of beams of light in different preset directions to form images to be processed, and a plurality of bandpass filters correspondingly arranged on the output sides of the plurality of beams of light used for forming said images, wherein the central wavelengths of the bandpass filters are respectively configured to be different wavebands of the reflected light from the surface of the object; the camera group comprises a plurality of cameras which are arranged behind the bandpass filters in a one-to-one correspondence mode and acquire filtered light beams; and the data processing module receives image information sent by the cameras, and performs compensation and photometric stereo reconstruction on the image information, so as to obtain surface features of the object. Further disclosed is a method implemented on the basis of the device.

The invention discloses a method for estimating total nitrogen of soil of different plough layers based on a field in-situ spectrum, and relates to the technical field of crop growth monitoring. Collecting soil samples of different plough layers in a field, and obtaining in-situ spectral data of soil; performing indoor analysis on the collected soil sample, and determining the total nitrogen content, the soil texture type and the porosity; classifying the soil samples according to the soil texture types, and respectively establishing correlation models between the total nitrogen contents of the soil with different textures and the in-situ spectral data; introducing a northern eagle optimization algorithm to improve a random forest and a generalized regression neural network to improve the prediction capability of the correlation model on the total nitrogen content of the deep soil; and constructing a comprehensive monitoring model by combining a surface spectrum inversion result and a soil vertical variation equation, so as to realize indirect high-precision estimation of the total nitrogen content of the soil in different plough layers. And a theoretical basis is provided for future soil total nitrogen deep monitoring model research, and a technical support and a theoretical decision are provided for rapid acquisition of deep soil nutrients in precision agriculture.

The present application relates to a geographic mosaicking method and apparatus for video images, and a computer device and a storage medium. The method comprises: acquiring real-time live streaming images of a real-world scene that are collected by a plurality of unmanned aerial vehicles, and GNSS information of the plurality of unmanned aerial vehicles; using a visual SLAM algorithm to perform input frame tracking on the real-time live streaming images, and performing pose estimation on successfully tracked input frames by combining visual trajectories and the GNSS information, so as to generate georeferenced camera poses; using the camera poses and a surface reconstruction algorithm to perform densification processing on the input frames, so as to generate a depth map of the real-world scene, and mapping the depth map into dense three-dimensional point clouds, so as to construct a three-dimensional surface model of the real-world scene; and using the camera pose and the three-dimensional surface model to perform orthorectification on the input frames, and integrating the orthorectified input frames into a global mosaicked map, so as to generate a global image of the real-world scene. By means of the embodiments of the present application, a real-time picture of a real-world scene can be quickly acquired, thereby providing robust support for a rapid emergency response in a real-world scene.

The invention discloses a method for adaptively identifying the thickness of a black soil layer based on a variational mode decomposition method and a ground penetrating radar technology, and the method can directly measure the thickness of the black soil layer of a large-area black land through the ground penetrating radar technology, automatically filters ground penetrating radar signal clutters, and corrects the ground position. According to the technical scheme, on the basis of a center frequency method and a residual error method, variational mode decomposition parameters suitable for black land ground penetrating radar signals are automatically obtained, then modal components of variational mode decomposition are subjected to counting analysis, a spectrogram of original ground penetrating radar signals and the actual black soil layer thickness are compared, an empirical model based on the peak area proportion is established, and the calculation accuracy is improved. The automatic screening can be used for identifying the post-screening center frequency and frequency sweep width of the thickness of the black soil layer, and the position of the black soil layer is adaptively identified after frequency filtering, so that the thickness of the black soil layer can be quickly obtained, and the identification accuracy and efficiency are improved.

The invention discloses a portable sedimentary rock classification system and method based on deep learning, and relates to the technical field of rock identification and geological survey. The system comprises a portable microscopic image acquisition module, a cloud deep learning model and a mobile terminal module. A user shoots macroscopic or microscopic images of sedimentary rocks through a mobile phone, the macroscopic or microscopic images are uploaded to a cloud end and then subjected to feature extraction and classification through the optimized ResNet50 model, and a classification result is fed back to a user end in real time. The innovation points comprise: (1) adopting a macroscopic and microscopic data set training model to significantly improve the classification precision; (2) designing a portable microscopic module to realize rapid acquisition of microscopic images; (3) mobile terminal identification service; and (4) the ResNet50 model based on residual network optimization supports high-precision fine-grained classification (sandstone, conglomerate, siltstone and clay rock). Experiments show that the system classification accuracy reaches 99% or above, and compared with a traditional laboratory method, the efficiency is greatly improved. The method can be widely applied to geological exploration, teaching and scientific research and science popularization scenes.

The invention relates to a modeling method, in particular to an unmanned aerial vehicle spectral image BRDF rapid acquisition and adaptive generalization modeling method. The method comprises the following steps: 1, determining a research area, obtaining multi-angle BRDF data of the research area, and obtaining illumination change data at the same time; 2, preprocessing the acquired multi-angle BRDF data in combination with illumination change data to obtain preprocessed multi-angle images, splicing the multi-angle images to generate a panorama of the research area, and acquiring a digital surface model graph at the same time; 3, carrying out pixel-by-pixel classification on the research area based on the panorama to obtain a ground feature category map; calculating the gradient and the slope direction of the research area pixel by pixel based on the digital surface model graph; 4, correcting a preset BRDF model by using the acquired illumination change data, gradient and slope direction; and 5, self-adaptive generalization modeling is carried out. According to the method, high-efficiency BRDF acquisition can be realized, and the influence of regional change, space environment and topographic factors on BRDF modeling precision can be eliminated.

The invention belongs to the technical field of guide rail defect detection, and particularly relates to a guide rail defect detection system and method based on image recognition, and the system comprises an image information collection module, an image information processing module, an image information transmission module, a feature information extraction module, a defect recognition and classification module and a detection result output module. According to the invention, rapid acquisition of guide rail defect images can be realized, the influence of external factors is considered, image acquisition equipment control, acquisition light source end control and equipment bearing end movement control are set, image acquisition can be completed more effectively and clearly, and a computer vision technology is utilized to complete preprocessing operation of image data, so that the processing efficiency is improved. And meanwhile, detection is completed by adopting a deep learning algorithm, various types of guide rail defects can be accurately identified and classified, and the detection precision is improved.

The invention discloses a preparation method of fresh taxus chinensis stem and leaf protoplasts. The preparation method comprises a preparation process and a purification process. The preparation method of the taxus chinensis stem and leaf protoplast is simple and easy to operate, raw materials are easy to obtain and low in price, reagent components have good biocompatibility, and the taxus chinensis stem and leaf protoplast is free of harmful components, safe and environmentally friendly. The invention provides a simple and rapid taxus chinensis stem and leaf protoplast enzymolysis preparation method, which adopts vacuum filtration, accelerates the permeation of enzymatic hydrolysate and improves the enzymolysis efficiency, so that the protoplast can be rapidly obtained. Meanwhile, high-purity separation of the protoplast is carried out in combination with density gradient sedimentation of the iodixanol solution, so that the protoplast with uniform size and complete form is obtained, and convenience is provided for scientific researches such as subsequent conversion and single cell transcriptome sequencing.

The utility model relates to the technical field of semiconductor wafers, and discloses a semiconductor wafer thickness measuring device, which comprises a moving assembly and a compression measuring assembly, the moving assembly is arranged below the compression measuring assembly, the moving assembly comprises a fixed bottom plate, the upper end of the fixed bottom plate is connected with a moving motor, and the moving motor is connected with the compression measuring assembly. The output end of the moving motor is fixedly connected with a threaded rod, the threaded rod is connected with a threaded block, the upper end of the threaded block is connected with a sliding block, and the sliding block is connected with a sliding groove. According to the utility model, the thickness information of a plurality of positions can be rapidly acquired, the flexibility during measurement is improved, the measurement work of the thickness of the whole wafer can be rapidly completed, the measurement efficiency is improved, different areas of the semiconductor wafer can be measured, the distribution condition of the thickness of the semiconductor wafer can be completely mastered, and the measurement accuracy is improved. And omission of areas possibly having abnormal thickness is avoided, so that the measurement is more comprehensive.

The invention discloses an unstructured road pit extraction method based on unmanned aerial vehicle point cloud data and optical image fusion. The method specifically comprises the steps of experimental data acquisition and preprocessing, road boundary fusion extraction, road pothole fusion extraction, image two-dimensional pothole crude extraction, point cloud three-dimensional pothole crude extraction, crude extraction pothole layered fusion, precision verification and the like. Aiming at the requirement of an automatic driving technology for safe production and transportation in an unstructured pavement, road data of a target area are quickly acquired through remote sensing of an unmanned aerial vehicle, texture and semantic information of an image and a three-dimensional geometric structure of point cloud are fully utilized, and a multi-layer fusion algorithm is designed to realize the safe production and transportation of the unstructured pavement. And high-precision and high-efficiency extraction of the unstructured road potholes is realized. The method is of great significance to automatic and stable driving of vehicles in the fields of logistics distribution, environmental sanitation operation, smart mines and the like.

The invention discloses a rapid identification method for ground-air combined analysis of a rock blasting effect, which is characterized by comprising the following steps of: collecting advantage information in a ground-air manner through an image processing technology of an unmanned aerial vehicle and an exploration vehicle, performing data comparison and calibration by taking the advantage information as a reference, and determining a muck pile area; establishing a visual three-dimensional explosion area by using a deep learning algorithm; then, the grade of rock in the muck pile area unit block is subjected to rapid field identification through the visual three-dimensional muck area; then estimating the rock grade of each unit block by using a distance power inverse ratio method according to the rock grade subjected to rapid field identification; and finally, estimating the rock grade of the whole muck pile area according to the rock grade of each unit block. By fusing the unmanned aerial vehicle and the all-terrain exploration unmanned vehicle, rapid acquisition and accurate analysis of the blasting muck pile particle size after open blasting are achieved, the efficiency and accuracy of blasting effect evaluation are remarkably improved, the problems of subjective errors and time consumption of a traditional method are solved, and technical support is provided for intelligent mine construction.

The present invention discloses a method for color three-dimensional reconstruction of large workpieces with complex shapes based on point cloud information for hand-eye calibration. By using a structured light binocular vision system in combination with image fusion, it is possible to achieve rapid acquisition of high-precision point cloud data while ensuring the accuracy of three-dimensional reconstruction, taking advantage of the flexible configuration and high measurement efficiency of the binocular structured light system. On this basis, a color camera is combined to endow the point cloud with real color texture feature information, and a robotic arm auxiliary module is combined to efficiently measure the point cloud data from multiple perspectives of the large workpiece. In addition, taking advantage of the fact that binocular vision can directly obtain point cloud information, the coordinate information of the point cloud is used to complete hand-eye calibration. Compared with traditional hand-eye calibration based on calibration plates, it directly and fully utilizes the advantages of point cloud data, avoids multiple coordinate system transformation processes, and the calibration process is more efficient and the accuracy is guaranteed.

The invention provides an environment document processing method and device based on a large model, equipment and a storage medium, and relates to the technical field of environment data processing. The method comprises the following steps: acquiring multi-source environment event document data; preprocessing the multi-source environment event document data; based on the task scene, performing feature extraction on the preprocessed text data by using a large language model to obtain text modal features, and extracting image modal features from the preprocessed image data by using a YOLO target detection algorithm; performing multi-modal feature adaptive fusion on the text modal features and the image modal features by adopting a dynamic weighting mode to obtain a cross-modal fusion vector; and constructing a knowledge graph based on the cross-modal fusion vector, and generating a multi-modal abstract. According to the method and the device, simple and logically clear abstracts can be generated for different types of documents, so that a user can quickly obtain core information of the documents, and the quick understanding requirement of multiple scenes is met.

The invention relates to the technical field of image acquisition, in particular to a non-contact visual defect acquisition system and defect detection method for disc scissors, comprising an image acquisition device and a control device electrically connected with the image acquisition device; the image acquisition device comprises a camera and an LED stroboscopic lamp, and by combining the stepping distance between acquisition frames and the acquisition position of the camera with the rotation speed of the disc shear tool, the image acquisition rhythm matched with the high-speed rotation of the disc shear tool can be realized, the detailed information of each part of the disc shear tool can be quickly acquired, and the image acquisition efficiency is improved; through matching of the PWM stroboscopic control frequency of the LED stroboscopic lamp and the exposure time of the camera, it is ensured that stable and appropriate illumination intensity and illumination time are provided when the camera is exposed every time, the problems of image blurring, inconsistent brightness and the like caused by uneven illumination or illumination change are solved, and the system is simple in structure, convenient to operate and low in cost. The problems that a traditional disc type cutter is low in detection efficiency, large in error and lagged in detection are effectively solved.

The invention provides a data processing method of a laser radar and a laser detection system. The data processing method comprises the following steps: S11, acquiring a frame of point cloud data of the laser radar; s12, determining a set of ground points in the frame of point cloud data; and S13, determining calibration parameters of the laser radar point cloud according to the set of ground points. In the embodiment of the invention, after the ground point set is extracted by using the GPU, the point cloud ground level is calibrated at a high speed, so that the radar 3D point cloud ground is aligned with the ground level of the physical world. According to the embodiment of the invention, the ground point in the 3D point cloud can be quickly obtained, the ground point is drawn by using the GPU, and the laser radar point cloud calibration parameter is obtained by using the projection of the ground point in the preset plane, so that the point cloud of the laser radar can be calibrated to be close to a world coordinate system and be basically aligned with the horizontal plane under the world coordinate system.

The embodiment of the invention relates to the technical field of space acquisition, and discloses a historical and cultural block three-dimensional space data rapid acquisition and display method, which comprises the following steps: acquiring multi-source three-dimensional space data of a historical and cultural block through a collaborative acquisition system; inputting the multi-source three-dimensional space data into a semantic data processing engine; in the semantic data processing engine, processing the multi-source three-dimensional space data to generate a digital twin model comprising semantic information; and presenting the digital twin model to a user through an interactive display platform and providing an interactive function based on semantic information. According to the method in the embodiment of the invention, multiple acquisition modes such as ground scanning, unmanned aerial vehicle aerial photography and handheld equipment detection can be integrated, large-range areas such as block roofs and high-altitude facilities can be quickly covered through the unmanned aerial vehicle, and blind areas of a single acquisition mode can be made up by depending on the handheld equipment to go deep into hidden corners such as narrow roadways. And the block can be comprehensively and abundantly displayed based on the semantic digital twinborn model.

The invention discloses an intelligent coordinate acquisition tool and system, and the tool comprises a mobile phone fusion positioning part which is internally provided with a coordinate acquisition system; the coordinate acquisition system comprises a workbench login unit, an acquisition task unit, a data acquisition unit, a data transmission unit, a data storage unit, a data processing unit, a high-precision positioning unit, a fusion positioning unit and a remote monitoring unit, and belongs to the technical field of coordinate acquisition. According to environment indexes, high-precision positioning and fusion positioning are intelligently switched, positioning information can be rapidly obtained in different complex environments, environment information, satellite signal strength and the like are analyzed in real time in combination with a data processing unit, and coordinate information is subjected to high-precision correction. According to the method, satellite positioning, base station positioning, wifi positioning and differential positioning are comprehensively applied, weight indexes of different positioning sources are obtained through data analysis, optimal positioning results are selected for fusion, and the positioning accuracy and adaptability are effectively improved.

The invention provides a high-speed traffic acquisition method based on a fused large model and related equipment, and relates to the technical field of natural language processing. The system utilizes the two models to start query processing at the same time, the cue word model directly and quickly obtains first traffic data based on intention parameters, and the plug-in model obtains more accurate second traffic data through dynamic arrangement and execution. When the second flow data is obtained, the system uses a more accurate query result; when the second flow data is not obtained, the system can still respond in time based on the first flow data. The two-channel parallel mechanism can obtain more accurate data in a more flexible question and answer mode during high-speed traffic, and ensures the accuracy of a query result and the stability of system response.

The present invention discloses an integrated air-ground intelligent highway inspection and patrol system, which relates to the field of highway inspection technology and includes an inspection and patrol management platform. The inspection and patrol management platform is communicatively connected to a data acquisition module, an environmental perception and analysis module, a target detection module, a disease target classification module, a pavement disease dynamic identification module, and an inspection and early warning management module. The data acquisition module is used to collect and pre-process various types of inspection data required for highway inspections. Through the coordinated operation of aerial inspections by drones and ground sensors, the present invention can quickly acquire inspection data over a large area, achieving all-round, real-time monitoring of highways, significantly improving inspection efficiency, and being able to complete large-scale inspection tasks in a short period of time, promptly identifying potential road disease problems, providing timely and accurate information support to road maintenance and management departments, and ensuring the safe and smooth operation of highways.

The invention belongs to the technical field of electric power monitoring and dispatching, and discloses a real-time electric quantity monitoring and dispatching management system, which realizes high-precision and real-time electric quantity and related parameter acquisition through a quantum sensing electric quantity acquisition unit, and ensures high-efficiency circulation of data from acquisition to processing by matching with a high-speed and stable transmission network of a global dynamic data transmission unit; the edge calculation preprocessing unit timely processes data and reduces delay, so that the system can quickly obtain the real-time state of the power grid, timely basis is provided for scheduling decision, and decision errors caused by data lag are effectively avoided; by adopting a modular design, each core unit can be flexibly combined and expanded, the quantum sensing electric quantity acquisition unit supports various communication protocols, and the global dynamic data transmission unit fuses various communication technologies, so that the requirements of different scales of power grids can be met, special interfaces and lines do not need to be customized, and the construction and maintenance cost is reduced; and the applicability of the system in a complex and changeable power environment is obviously improved.

The invention provides a control system and method for a Fourier interference infrared spectral imaging remote sensing instrument, and relates to the technical field of infrared remote sensing, and the system comprises a main control module, a sub-control module, a control interface, an execution element and a spectral imaging display system. And the main control module is used for controlling the sub-control module to control the execution element through the control interface according to a logic process set by a program so as to obtain Fourier interference infrared spectral imaging remote sensing data of an observation target, and completing display and control functions of a human-computer interaction interface through the spectral imaging display system. According to the invention, centralized control management of an optical-mechanical-electrical-thermal whole system of an instrument is realized, automatic work and operation of a remote sensing instrument system are realized, and rapid acquisition and analysis of Fourier interference infrared spectrum imaging are realized by using an area array detector.

The invention relates to the technical field of tree information acquisition, in particular to an urban tree information rapid acquisition method and system, and the method comprises the following steps: obtaining the geographic coordinates of each tree in a city through a GNSS receiver, recording the accuracy and timestamp information of each position, executing data synchronization, and generating urban tree coordinate data. According to the method, the GNSS receiver and the microwave remote sensing equipment are introduced, high-precision and multi-dimensional analysis of tree data is ensured, the GNSS receiver provides accurate coordinates and timestamps, the real-time performance and accuracy of geographic data are enhanced, and the microwave remote sensing technology accurately evaluates the age and health condition of the tree by analyzing the dielectric constant of the tree, so that the reliability of the tree is improved. The image sensor capable of automatically adjusting the focal length and the exposure parameters can capture the color and the shape of the leaves in detail, the detail degree and the accuracy of disease and insect pest diagnosis are improved, tree information mapping is updated in real time, the efficiency of environment monitoring and urban planning is improved, and powerful support is provided for management of an urban ecological system.

The invention provides a fault data processing method and device, computer equipment and a storage medium, and belongs to the technical field of computers. According to the method, the variable name, the data length and the data address of the snapshot data needing to be stored are put into the snapshot information array during initialization, so that when fault data are stored, the snapshot information when the fault occurs can be directly stored into the nonvolatile storage area according to the address associated with the fault diagnosis code list, and the fault diagnosis efficiency is improved. And the storage efficiency of the fault data is greatly improved. In a similar way, the fault data is quickly acquired according to the address associated with the diagnosis fault code list when being read, so that the reading efficiency is improved.

The invention discloses a foreign trade information processing method and system, and relates to the technical field of foreign trade. The method comprises the following steps: S1, collecting foreign trade information from various foreign trade platforms, industry websites, customs databases and other channels by using a web crawler technology; s2, acquiring internal information such as order data, customer feedback and inventory conditions of an enterprise through docking with an internal system of a foreign trade enterprise; and S3, cleaning the collected information, and removing repeated, wrong and irrelevant data. According to the method, the web crawler technology is utilized, foreign trade information can be automatically collected from multiple channels, multiple aspects of suppliers, products, markets, policies and the like are covered, the crawler units have the ability of self-adaption to website structure changes, the continuity and accuracy of information collection are ensured, the efficiency and quality of information collection are greatly improved, and the method is suitable for popularization and application. Foreign trade enterprises can quickly obtain comprehensive and accurate market information.

The invention belongs to the technical field of crop disease and insect pest detection, and discloses a method and a system for classifying, identifying and detecting crop disease and insect pests. According to the method, the lightweight and efficient FasterNet is adopted as the preliminary classifier, so that crop diseases, insect pests and weeds can be quickly and accurately distinguished, and the classification precision is improved. And secondly, for a disease image, through a segmentation model based on deep semantic segmentation and by adopting a double-stage segmentation strategy, respectively segmenting a leaf region and a scab region, thereby realizing high-precision segmentation and facilitating subsequent severity diagnosis and quantitative analysis. And for an insect pest image, utilizing a YOLOv11 target detection network to accurately select an insect pest position and identify an insect pest type. For a weed damage image, the YOLOv11 target detection network is also used to identify a weed area, and rapid acquisition and positioning of a field weed distribution condition are realized. According to the invention, the lightweight network and the efficient detection architecture are introduced, the recognition precision and the reasoning speed are both considered, and the dual requirements for real-time performance and reliability in field application of farmland can be met.

The present invention discloses a variable beam divergence angle laser communication terminal and a rapid acquisition method thereof, belonging to the technical field of optical communication devices, including a main telescope, a fine tracking fast steering mirror, a beam splitter, a filter, a beam splitter, a beacon receiving lens group, a beacon detector, a signal transmitting mirror group, a pre-aiming fast steering mirror, a signal receiving mirror group, a receiving fiber amplifier, a multi-core fiber splitter, an optical switch, and a transmitting fiber amplifier, which constitute a signal light transmitting optical path, a beacon light receiving optical path, and a signal light receiving optical path; the signal light transmitting optical path provides a transmitting beam through different mode field fibers, and uses different paths of the transmitting mirror group to shape and variably beam-divergence emit the transmitted light, the signal light receiving optical path is used to collect, shape, couple, and optically amplify the input signal light, and the beacon light receiving optical path is used to collect, shape, converge the input signal light, and use an image positioning detector to position the target light spot. The present invention can improve the efficiency of long-distance acquisition.