27results about How to "Reduce identification costs" patented technology

The invention relates to the technical field of RFID chip manufacturing, in particular to an RFID chip image anomaly detection method and system based on intelligent learning. The method comprises the following steps: acquiring a real-time RFID chip sampling image set, performing feature alignment based on a registration template, generating an average grey-scale map by using an alignment image set, and obtaining a chip edge mask image set by using an edge search algorithm; segmenting the edge mask image set of the RFID chip to obtain an effective edge mask variance image set of the RFID chip; integrating the variance image set to obtain a pre-generated variance image; acquiring field environment data of the RFID chip and performing sensitivity coefficient estimation to obtain an edge sensitivity coefficient; and performing convolution filtering smoothing processing on the pre-generated variance image to obtain a chip edge variance image, and constructing an RFID chip image anomaly detection model based on the edge variance image and the average grey-scale image. According to the invention, the detection accuracy and stability are improved.

The invention belongs to the technical field of agricultural biology, and relates to a rice high-yield salt-tolerant molecular marker and application thereof. The rice high-yield salt-tolerant molecular marker is located at the 615th and 560th sites of chromosome 6 of a rice reference genome IRGSP1.0, and the polymorphic site is G / A. The invention further discloses a preparation method of the rice high-yield salt-tolerant molecular marker. The high-yield and salt-tolerant characteristics of the germplasm carrying the A nucleotide allelic variation at the site are obviously lower than those of the germplasm carrying the G nucleotide allelic variation, specifically, the yield of the GG genotype is the highest, the yield of the GA genotype is the middle, and the yield of the AA genotype is the lowest. By utilizing the molecular marker and the corresponding identification method, the genotype can be accurately and rapidly identified in the accurate design of the high-yield salt-tolerant rice, the phenotype identification cost of a field test in the later period is reduced, and the application of an accurate design technology of the rice in breeding is promoted.

A head-removed shrimp posture detection method based on machine vision comprises the following steps: carrying out three-channel separation on a head-removed shrimp image in an HSV space, and selecting an optimal channel according to a foreground and background difference to obtain a head-removed shrimp binary image; obtaining three distance transformation heat maps of the binarized image of the head-removed shrimp, and selecting an optimal heat map according to the extraction matching degree of the central area of the shrimp head to obtain a central area image of the shrimp head; performing corner detection on the prawn head center area image, and fitting corner coordinates through a straight line to obtain a prawn head and prawn back orientation datum line; comparing the distances between the two wide sides of the minimum enclosing rectangle of the binarized image of the head-removed shrimp and the two end points of the shrimp head orientation datum line to obtain a shrimp head orientation vector; comparing the distance between the long side, tightly attached to the shrimp back, in the minimum bounding rectangle of the binarized image of the head-removed shrimp and the two end points of the shrimp back orientation datum line to obtain a shrimp back orientation vector; and the orientation vectors of the shrimp head and the shrimp back represent the attitude information of the head-removed shrimp. The method can accurately and stably detect the postures of the head-removed shrimps at low cost, and belongs to the shrimp posture image processing technology.

The disclosed embodiments relate to a method for identifying user intent, an interaction method, an apparatus, a system, a device, and a medium, wherein the method for identifying user intent may include: obtaining a user request sentence to be identified; obtaining at least one user intent sample that matches the user request sentence according to a text similarity algorithm; and determining the user intent implied in the user request sentence from at least one user intent sample according to a sentence implication model. The technical solution provided by the disclosed embodiments does not require the construction of a large number of user sentence samples and the annotation of a large number of user intents during the process of identifying user intent, and the cost of identifying user intent is low. At the same time, the solution has high generalization and can be applied to any intelligent interaction scenario that requires identifying user intent.

This invention discloses a device type identification method, terminal device, and storage medium based on traffic sampling. It eliminates the need to collect complete device traffic data; device identification is achieved simply by sampling traffic at the gateway. To address the issue of missing traffic features, traditional tensor imputation algorithms learn the embeddings corresponding to tensor rows, columns, and depths, but cannot generalize to unknown rows, columns, or depths. This results in repeated retraining, time-consuming and costly feature imputation. This invention proposes an inductive tensor imputation method that utilizes historical information to learn and generate embedding functions, enabling fast and effective device traffic feature imputation.

This invention belongs to the technical field of bird diversity monitoring equipment, specifically relating to an identification device for assessing bird species diversity in protected areas or habitats. It includes an installation unit, a monitoring unit located at the top of the installation unit, and a lidar located at the top of the monitoring unit. The monitoring unit and the lidar are controlled to rotate by motor one and motor two, respectively, to monitor bird activity. An infrared camera is mounted on the outer end face of the monitoring unit, and a lens cleaning mechanism and a liquid storage tank are located at the top of the infrared camera. This invention enables motor two to drive the lidar to monitor bird spatial location information in real time, while simultaneously coordinating with a pressurization component to pressurize the liquid channel within the lens cleaning mechanism. This allows the cleaning fluid to be periodically sprayed out, achieving periodic self-cleaning of the infrared camera lens. This eliminates the need for an external spray nozzle control circuit and program, reducing device cost and overall power consumption, and increasing the outdoor operating time of the identification device.

This application relates to a method and apparatus for recognizing the display shape of tobacco and fast-moving consumer goods, including acquiring an image to be detected and performing product location recognition and product specification recognition to obtain location and specification recognition results that represent the location and specification information of each product; determining the global boundary points and minimum bounding rectangle of the product area in the image to be detected based on the location and specification recognition results, performing perspective transformation on the image to be detected based on the global boundary points and minimum bounding rectangle to obtain geometric correction results; performing cluster analysis on the products based on the geometric correction results, constructing a grid canvas based on the cluster analysis results to obtain grid construction results; determining the product whose specification information represents the target specification as the target product based on the location and specification recognition results and the grid construction results, and determining whether the actual display shape of the target product conforms to the target display shape based on the unique location of the target product to obtain the display shape recognition result.

A crude oil identification method and device based on structure-oriented lumping, the method comprising: obtaining multiple property values of crude oil to be identified from a calibration report of crude oil detection; analyzing the multiple property values of the crude oil in combination with a first molecular structure database established in advance to determine SOL molecular structure data of the crude oil; comparing the SOL molecular structure data of the crude oil with SOL molecular structure data in a second molecular structure database established in advance to determine a crude oil sample with the maximum similarity; and taking the crude oil sample with the maximum similarity as an identification result.

This invention relates to the field of lithology identification methods, specifically a method and apparatus for identifying lithology in tight gravelly sandstone reservoirs through well logging. The method includes: determining key sensitive parameters for different lithologies within a target tight gravelly sandstone reservoir; establishing Q-models for specific lithologies and other lithologies based on the key sensitive parameters; identifying samples of specific lithologies based on the Q-models for those lithologies; and identifying samples of other lithologies based on the Q-models for those lithologies. This invention achieves precise identification and quantitative characterization of lithology in tight gravelly sandstone reservoirs, providing an intuitive and effective reference for subsequent calculations of tight reservoir parameters. It enables the identification and characterization of lithology using conventional well logging data, significantly improving the efficiency and reducing the cost of well logging interpretation.

The application discloses a kind of enterprise carbon management level evaluation methods, it is related to enterprise carbon management level evaluation technical field, existing enterprise carbon neutral management system has not been established, lack clear enterprise carbon neutral development evaluation framework;Existing enterprise disclosure type document identification extraction efficiency is poor.The present application provides a kind of enterprise carbon management level evaluation method, adopts the double-channel fusion architecture of original text fast channel, multi-modal visual identification main channel, and channel decision is carried out to each page respectively;Through multidimensional quality heuristic determination to original text flow, the page of insufficient reliability is automatically abandoned, and visual identification is turned into;Identification cost is significantly reduced, and identification stability is improved;Build the enterprise carbon neutral management and development CROCS model including sure carbon, carbon reduction, carbon offset, carbon emission and carbon stimulation five modules;Based on the model, the development of enterprise carbon neutral is evaluated.

The invention discloses a specific SNP (Single Nucleotide Polymorphism) locus combination for identifying red and white pitaya and hybrids, which comprises 10 SNP loci, and the 10 SNP loci are obtained by screening through multiple standards such as FST, allele frequency difference and LD pruning on the basis of SLAF-seq data of 45 core germplasms. The specific SNP site combination can be used for accurately distinguishing red-pulp pitaya, white-pulp pitaya and filial generations thereof, the problem of germplasm identification caused by phenotype confusion and interspecific hybridization is solved, and an accurate, efficient and low-cost molecular identification tool is provided for pitaya germplasm resource management, parent selection, molecular breeding and the like. The invention also discloses a primer for amplifying the specific SNP sites and application of the specific SNP site combination.

This invention provides a method, apparatus, electronic device, and storage medium for detecting rolled materials. The method involves acquiring the center of the side boundary of the rolled material, scanning the side boundary along any direction from the center to obtain marker point and contour point data, fitting the contour point data to a reference line in the corresponding direction based on the marker points, and performing multiple straight line fittings on the contour point data using the reference line as a reference to obtain multiple fitted straight lines. The roll state is determined based on the reference line and the fitted straight lines. This application reduces labor costs by automatically detecting the contour point data of rolled materials. By fitting the shape of the rolled material to the contour point data, multiple fitted straight lines are obtained. The roll state of the rolled material is judged based on the relationship between the straight lines, and the output results are directly transmitted to subsequent processes, facilitating adjustments by the robot and improving production efficiency.

The embodiment of the invention discloses a charging pile identification method and device. According to the method, charging messages reported in the charging process of a to-be-identified charging pile are analyzed, a multi-gun parallel charging self-checking result is stored as to-be-rechecked charging messages, and when the number of the to-be-rechecked charging messages is larger than a preset number, the to-be-rechecked charging messages are reversely checked to determine a corresponding target charging order. And if the average current value of the target charging order is greater than a preset current value, determining that the target charging order is a multi-gun parallel charging order, and when the number of the multi-gun parallel charging orders corresponding to the to-be-identified charging pile is greater than a preset order number, determining that the to-be-identified charging pile supports multi-gun parallel charging. According to the method, whether the to-be-identified charging pile supports multi-gun parallel charging is automatically identified based on the charging message reported by the to-be-identified charging pile, so that the process of field inspection and identification of operation and maintenance personnel is omitted, the identification cost is reduced, and appropriate charging piles are matched for different types of vehicles according to the identification result.

This invention discloses a vehicle speeding identification method, device, equipment, and storage medium. The method includes: when a vehicle is detected traveling on the road, determining the vehicle's position offset within a target time period based on the vehicle's position coordinates in a target coordinate system at different times; determining the vehicle's positioning interval time; determining the driving speed at each stage based on the positioning interval time and the vehicle's position offset within the target time period; determining the current driving speed based on the vehicle's position offset within the target time period; and comprehensively identifying the vehicle as speeding based on the driving speed at each stage and the current driving speed. By using the above method, determining the vehicle's position offset within the target time period based on its position coordinates at different times, determining the current driving speed, and determining the driving speed at each stage based on the positioning interval time, and then comprehensively identifying the vehicle as speeding based on the target speed limit, the accuracy of identifying vehicle speeding can be effectively improved, and the identification cost can be reduced.

The invention relates to a low-resistivity oil reservoir identification method, and belongs to the field of low-resistivity oil reservoir identification, and the low-resistivity oil reservoir identification method comprises the steps: obtaining the porosity, resistivity and historical oil test and production test data in historical drilling data, building a corresponding physical property-electrical property-oil content relation chart for each sedimentary microfacies by using the data, and obtaining the corresponding physical property-electrical property-oil content relation chart for each sedimentary microfacies; acquiring a porosity lower limit and a resistivity lower limit corresponding to the oil reservoir under each sedimentary microfacies through the drawing board, and taking the porosity lower limit and the resistivity lower limit as standards for determining whether the corresponding sedimentary microfacies reservoir contains oil or not; different identification standards are set for different sedimentary microfacies reservoirs, so that the identification accuracy of the low-resistivity oil reservoir is improved.

The invention relates to the technical field of PCB batch management, in particular to a method and system for identifying mixed batches of PCBs, electronic equipment and a medium, and the method comprises the following steps: distributing a detection through hole identifier for each batch of PCBs; the method comprises the following steps: acquiring panorama images of to-be-tested PCBs in batches, and sequentially performing graying and binarization processing on the panorama images; carrying out image registration and difference operation on any group of binarized images in the binarized images of the PCBs to be detected in batches to obtain a difference image; dividing the PCB to be detected corresponding to the full-homodyne image into the same batch, marking a feature identifier on the corresponding binary image, performing similarity analysis on the non-homodyne image to obtain a similarity analysis value, and performing batch identification based on the similarity analysis value and the feature identifier corresponding to the binary image; and outputting batch identification results of the to-be-detected PCBs in batches. Through batch detection, the detection efficiency is higher, and the batch identification requirement of PCBs of the same size can be met.

The present application relates to the field of artificial intelligence technology, and specifically discloses an iris recognition method and device, wherein the method comprises: obtaining standardized three-dimensional iris image data of an iris to be recognized; using a two-dimensional convolutional neural network to extract and classify features of the standardized three-dimensional iris image data, and obtaining target feature data and a target user label corresponding to the iris to be recognized, wherein the two-dimensional convolutional neural network comprises a three-dimensional image processing layer, and the three-dimensional image processing layer performs dimensionality reduction processing on the standardized three-dimensional iris image data to obtain multiple two-dimensional iris image data, and the multiple two-dimensional iris image data include oblique section data; retrieving iris feature data corresponding to the target user label from a three-dimensional iris image database, wherein the three-dimensional iris image database stores iris feature data of each user among multiple users; generating an iris recognition result according to the target feature data and the retrieved iris feature data. The above scheme can improve the accuracy of iris recognition.

The application provides an element recognition point data processing method and device, electronic equipment and a storage medium, relates to the technical field of electronic maps, can be applied to various scenes such as cloud technology, artificial intelligence, intelligent transportation and auxiliary driving, and the method comprises the following steps: receiving recognition point data of a road image reported by a terminal; performing initial aggregation processing on the recognition point data based on a time sequence to obtain a plurality of recognition point sequences; extracting a recognition point subsequence corresponding to an element label of at least one element type from each recognition point sequence of the plurality of recognition point sequences; determining a recognition target difference and an image time difference between two adjacent recognition point data in the recognition point subsequence; and performing same element aggregation on the recognition point data in the recognition point subsequence according to the recognition target difference, the image time difference and an element similarity condition to obtain a target sequence segment corresponding to the recognition point subsequence. The application can ensure the coverage and integrity of road elements and reduce the cost of the terminal.

The invention provides a japonica rice sheath blight resistance identification method, and belongs to the technical field of plant disease resistance identification. The invention provides a method for identifying the sheath blight resistance of japonica rice. The method comprises the following steps: planting and culturing japonica rice seeds to be detected in an intelligent greenhouse, performing sheath blight induction from a tillering end stage to a young ear differentiation stage, observing the attack condition of the sheath blight, measuring the average scab length of the japonica rice to be detected, calculating the disease index, and evaluating the sheath blight disease grade of the japonica rice. According to the method, the japonica rice rapidly enters the tillering last stage, the plant requirement of sheath blight identification is met, and the identification period is remarkably shortened; the method can complete simultaneous identification of multiple varieties at the same time, is not limited by other conditions in the field, and reduces the influence of environmental factors, thereby improving the accuracy and repeatability of sheath blight resistance screening. The banded sclerotial blight identification can be carried out for 3-4 times in one year, the dependence on professional equipment and large-area test fields is reduced, the method is more economical and universal, the identification efficiency is improved, and the identification cost is reduced.

The present invention discloses a method for automatically identifying the welding position of a large workpiece to be welded. The method mainly reconstructs the unit model of the large workpiece to be welded by using the PointNetLK++ point cloud registration network model that adds a spatial attention mechanism and a channel attention mechanism on the basis of the PointNetLK network model, and the point cloud data converted from the images of the large workpiece to be welded at different angles collected by a binocular camera, and then extracts the boundary points of the welding model using the gradient change of the normal vector, and then further selects the points to be welded according to the distance from the points at the intersection to different planes, so as to accurately identify the welding position of the workpiece to be welded. The present invention not only effectively reduces the recognition cost, but also greatly improves the accuracy of the three-dimensional reconstruction of large welding models and the accuracy of the recognition of the position to be welded. At the same time, it facilitates the operation and management of welding operations by technicians.

The present invention relates to a primer composition for identifying the purity of "Hetian No. 3" corn seeds and a method for identifying the purity of "Hetian No. 3" corn seeds using the primer composition. The identification method of the present invention directly analyzes the genetic material DNA of the target object, and the result does not depend on the technician's understanding of the agronomic traits of the sample, nor is it affected by the environment. It solves the problem of data inaccuracy caused by human factors and environmental factors in the previous technology, saves identification costs, shortens identification time, and is more accurate and reliable for the identification of new varieties.

The invention belongs to the technical field of plant grafting, and particularly relates to an early identification method for healing degree and affinity of fruit tree grafted rootstocks and scions. The early identification method comprises the following steps: grafting a scion to a stock, culturing for 10-20 days, inserting the base part of the stock into a fast green staining solution for staining, and judging the healing degree and affinity according to the staining condition. Different rootstock and scion combinations after grafting are dyed by using the dyeing agent fast green, the transportation difference of the fast green in the grafted rootstock and scion combinations is analyzed, the rootstock and scion healing degree and affinity can be rapidly judged, and technical and theoretical supports are provided for rapid rootstock breeding, rootstock and scion combination screening and rootstock application.

This invention discloses an active injection-type fault nature identification method for wind farms connected to the grid via flexible DC transmission lines, belonging to the field of power system relay protection technology. S1. After a fault occurs, the sending-end MMC converter station detects a change in the circuit breaker state, exits the original V-f control strategy, and sets the modulation wave to zero, causing power loss on the AC side of the sending-end MMC converter station; S2. After waiting for the fault arc extinction time, the circuit breaker is reclosed, establishing a current injection channel; S3. The sending-end MMC converter station outputs a three-phase symmetrical sinusoidal modulation wave, which is processed to generate a switching signal, activating the capacitors of each phase bridge arm submodule, injecting a voltage detection signal into the AC side of the faulty line; S4. Based on the difference in the amplitude of the current signal generated by the voltage detection signal, the fault nature of the line is identified. This invention can accurately identify the fault nature of wind farms connected to the grid via flexible DC transmission lines, shorten power restoration time, improve system operational reliability, avoid overcurrent during the identification process in the event of severe faults, and has high sensitivity to high-resistance faults.

The present invention relates to the field of image recognition technology, and discloses a method, device, equipment and storage medium for identifying the on- and off-block times of flights. The method for identifying the on- and off-block times of flights comprises: collecting video images fixedly shot at the aircraft parking position at preset time intervals; inputting the video images into a pre-trained aircraft recognition model for recognition, and outputting the circumscribed rectangular coordinate frame of the recognized target aircraft; calculating the first overlap value and the second overlap value of the circumscribed rectangular coordinate frame of the target aircraft and the preset reference circumscribed rectangular coordinate frame based on a preset overlap value calculation formula; recording the first time node when the first overlap value is valid and the second time node when the second overlap value is valid; based on the first time node and the second time node, determining the on-block time or off-block time of the target aircraft. The present invention realizes the automatic recognition of the on- and off-block times of aircraft, reduces the recognition cost, and improves the efficiency and accuracy of recording.

The invention provides a target identification method and device, electronic equipment, a storage medium and a vehicle, and relates to the technical field of vehicles. The method comprises the following steps: acquiring laser radar data, wherein the laser radar data comprises environment information or position information of a laser radar; according to the point cloud feedback information, determining a first view area corresponding to the laser radar data and a first angular resolution corresponding to the first view area; according to the first angular resolution, the target object in the first visual field area is recognized, only the angular resolution of the ground area and the angular resolution of the area of interest are needed in the recognition process of the target object, the angular resolution of the sky area or the non-attention area does not need to be considered, redundancy of the visual field area is avoided, the recognition cost is reduced, and the recognition efficiency is improved.

The invention discloses a detection method and system for a complex ground random target, and the method comprises the steps: carrying out the data collection of a complex ground through collection equipment, and obtaining initial collection data; the data acquisition device at least comprises a hyperspectral acquisition device, an SAR acquisition device and a camera acquisition device; performing feature marking on the initial acquisition data acquired by the camera acquisition equipment; if the feature mark exists, carrying out detection and identification to obtain a detection result, and stopping carrying out detection and identification on initial acquisition data acquired by the hyperspectral acquisition equipment and the SAR acquisition equipment; and if no feature mark exists, performing consistency processing, normalization processing and detection identification on the initial acquisition data acquired by the hyperspectral acquisition device and the SAR acquisition device to obtain a detection result. In the invention, two channels are identified and detected, the identification efficiency is not influenced, and the identification cost is obviously reduced.

The invention relates to the field of molecular structure mass spectrum analysis, in particular to a phencyclidine and analogue structure analysis method based on EI mass spectrum. The method comprises the following steps: acquiring a characteristic ion sequence of a suspicious object in an EI mass spectrum mode; s30, judging whether the characteristic ion sequence meets the conditions of phencyclidine and analogues thereof or not, and if yes, turning to the step S30; if not, determining that the suspicious object is not phencyclidine and analogues thereof, and ending the analysis; judging the structures of pyrrolidine and piperidine in the suspicious object according to the characteristic ion M6; according to the characteristic ion M5, judging the structures of the thiophene ring and the benzene ring in the suspicious object; if yes, turning to step S40; if not, reducing the structure of the compound, and ending the analysis; the equation (1) and the equation (2) are solved according to the characteristic ion sequence, the results of x and y are obtained, x represents CH2, y represents O, and the structure of R in the suspicious object is judged; and restoring the suspicious object structure, and ending the analysis.