71results about How to "Maintain continuity" patented technology

The invention discloses a user track privacy protection method and system fusing a generative model and three-stage personalized differential privacy, and relates to the technical field of data security, and the method comprises the steps: obtaining real user track data, and carrying out the preprocessing of the real user track data to form standardized track representation; training a depth generation model to generate synthetic trajectory data; performing density clustering on the synthetic trajectory to obtain a feature region and calculating a region centroid; point-level privacy budgets are distributed according to three stages of the area proportion, the centroid distance and the global density; constructing an adaptive elliptical disturbance domain based on the regional covariance, sampling candidate confusion points in the disturbance domain and applying road feasibility screening; and calculating a score based on the privacy budget and the utility function, and sampling replacement points by adopting an index mechanism to output a privacy protection trajectory. According to the technical scheme, the track structure continuity and the road semantic consistency are remarkably improved under the condition that the differential privacy constraint is met, and the privacy intensity and the data availability are both considered.

The invention discloses a cold-chain pork quality dynamic evaluation method and system based on multi-source data fusion, and relates to the technical field of data processing and intelligent evaluation, and the method comprises the following steps: collecting multi-source signal information of a whole cold-chain transportation process, sorting according to a unified time sequence, continuously arranging all signals on a time axis, and carrying out data processing on all the signals; a complete dynamic record is formed; and extracting each time interval and signal amplitude change track from the formed dynamic record, analyzing a signal section with repeated wave crests in a short time, and generating a preliminary data manuscript for reflection interference judgment. According to the invention, through time sequence arrangement and dynamic association of multi-source signals, a wave crest track analysis mechanism is constructed, real-time identification and correction of reflection interference are realized, and continuity and accuracy of a gas concentration curve are ensured; and by generating a reflection source position list and adjusting numerical value distribution of repeated fragments, false fluctuation is eliminated, and the stability and reliability of cold-chain pork quality evaluation are improved.

The invention discloses a pavement crack accurate extraction method and system based on multi-scale image segmentation, and belongs to the technical field of pavement detection, and the method comprises the steps: obtaining a to-be-detected pavement image, carrying out the brightness normalization and geometric correction of the pavement image, and constructing a multi-scale image set with different resolutions; generating a spatial texture channel and a spectral domain response channel for each scale image in the multi-scale image set, and fusing the spatial texture channel and the spectral domain response channel to obtain a spectral-space coupling input tensor, wherein the spectral domain response channel is obtained by extracting energy characteristics of a plurality of frequency bands after performing spectrum transformation on the scale image; a multi-scale image set is constructed for road surface images, and coupling expression of spatial texture information and spectral domain response information is introduced, so that feature consistency of fine cracks under different resolutions is enhanced, and scale drift and response distortion caused by shadows, light reflection and seam textures are inhibited at the same time; therefore, the separability and the stability of the crack in a complex scene are improved.

The present application relates to the technical field of industrial sewing visual control, in particular to a threading and back threading control method and system based on visual identification, comprising: acquiring a multi-view monitoring image sequence in real time through a high-definition industrial camera, obtaining visual data of a sewing needle, a sewing thread, cloth and a reference point through image enhancement and feature extraction. An improved algorithm is used to combine the sewing thread material and the cloth texture to construct a physical travel constraint model, generate an optimal threading path and convert it into a servo control instruction. The sewing thread deviation, tension abnormality and sewing needle drift are detected in real time, the correction amount is calculated according to the deviation vector and the cloth state, and the trajectory is re-planned. When the thread is broken or wound, the fault point is located through vision, and a back threading path that bypasses the obstacle area is planned. The present application improves the adaptability of the path to the actual working condition, realizes dynamic closed-loop correction, reduces the threading deviation and tension fluctuation, avoids secondary interference in the back threading process, and ensures stable and accurate execution of the threading and back threading actions.

The utility model discloses a filter device of circulating backwash, including filter casing, install a set of bearing seat in the inner chamber of filter casing upper end, bearing seat is sealed with a set of filter core rotation connection, and the rotation action can be realized to filter core through drive assembly, and cooperate transmission assembly and drive cleaning brush rotation, the utility model centrifugal force throws out high -speed water flow, and the impact force of impurity is greatly promoted, and the mechanical cleaning of cooperation cleaning brush, under double effect, can more efficiently remove strong viscosity, firmly attached contaminant and deep pore small impurity, and backwash efficiency improves obviously, and high -efficient backwash reduces backwash frequency and time, and water flow energy consumption is reduced, simultaneously, the filter core is because clean thoroughly, and the service life is extended, and the frequency of replacement is reduced, and the overall operation cost is reduced.

The present application relates to the field of noise reduction technology, in particular to a kind of adaptive noise reduction method, system and equipment, wherein the method comprises: obtaining mixed audio signal and dividing into short-time segment, after normalizing short-time segment, the normalized short-time energy and normalized change intensity of short-time segment are calculated, the short-time segment after normalization is converted into spectrogram and input into light time-frequency feature extraction network, and noise state feature set is output by extraction network;The comprehensive score of short-time segment in noise state feature set is calculated, the starting segment of change, the change influence range and the change type are determined, and the state change description of noise is constructed;The normalized processing intensity of state change description is calculated, noise reduction execution item is constructed, noise reduction execution scheme is generated by sorting noise reduction execution item;For each noise reduction execution item in noise reduction execution scheme, time-domain audio is overlapped and spliced according to the original time sequence of short-time segment, and noise reduction output signal is output.

The embodiment of the invention provides a video generation method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of artificial intelligence. According to the method, a reference image and a text cue word are obtained, and a complete background image, an external expansion background image and a target object image are generated according to the reference image, so that the generation of a video clip depends on a unified and expanded background reference, and the structure and color continuity of a background region is kept in a segmentation generation process; on the basis, multi-stage background modeling of a complete background image and an external expansion background image is combined, so that background consistency of the generated video clip is kept, and dynamic change of the target object under rich semantic guidance is realized. The continuous and complete video content is obtained after splicing, the static and steady state characteristics of the background can be maintained, the cross-segment background texture and hue drift can be significantly reduced, and the stable presentation of the background area under the main body action change can be realized.

The invention relates to an enterprise collaborative office management method and system, and relates to the technical field of enterprise management, and the method comprises the steps: obtaining resource use data in enterprise office; analyzing the resource use data through a threshold judgment model, and when the value of the resource use data exceeds a preset threshold, executing a resource allocation algorithm to minimize the total resource allocation deviation and load imbalance; in response to completion of execution of the resource allocation algorithm, sending an adjustment instruction to the cloud resource management platform, and adding resource allocation to the server of the enterprise; obtaining and analyzing workflow data of an enterprise, and identifying project delay factors to obtain a corresponding analysis result; according to the analysis result, executing a workflow adjustment algorithm to minimize task delay and task load imbalance; and analyzing the event mode in the working data flow, and executing an event response algorithm to optimize the event mode so as to maximize the event response efficiency and the resource utilization rate. The office management effect of an enterprise system can be improved.

The application discloses a kind of fracture network multi-step iteration deep learning prediction methods for concealed rock mass, it is related to geological fracture structure intelligent identification and prediction technical field, including, extraction exposed rock area fracture network image, analysis exposed rock area in exposed rock mass fracture network image geometric characteristic parameter;Based on geometric characteristic parameter, exposed rock mass fracture network image is divided into different continuous sequence images, according to continuous sequence image construction training set and verification set;Deep learning neural network model is constructed, and training set and verification set are used to execute training process;Different image block size of continuous sequence image and adjacent sequence overlap rate are set as multiple candidate combinations, generate corresponding training set and verification set for each candidate combination, train and verify deep learning neural network model.Deep learning neural network model is constructed to predict the fracture network in concealed area, realize the continuous extrapolation of the fracture structure in masked area, and reduce the cumulative effect of prediction error.

The invention provides an autonomous decision-making system and method for an unmanned ship, and relates to the field of intelligent control systems. The system comprises a decision-making machine module, a skill application module and a communication interaction module, wherein the decision-making machine module is used for receiving a navigation task instruction from a ground station, determining a corresponding navigation task type based on the navigation task instruction, generating a decision-making control instruction for uniformly scheduling navigation of the unmanned ship, and performing event generation, event judgment and interruption control based on navigation state information in the navigation process of the unmanned ship; the skill application module is used for executing corresponding navigation operation under the control of the decision control instruction, and monitoring and reporting navigation state information in the execution process; and the communication interaction module is used for realizing two-way communication among the modules. The method is used in the autonomous decision-making process of the unmanned ship, and solves the technical problem that when a navigation task is executed in a complex environment in the prior art, people cannot be flexibly simulated for decision-making control.

This invention provides a laser SLAM inspection vehicle and method suitable for complex underground infrastructure environments. A multi-line lidar system is equipped with multiple laser emission and reception channels to generate high-density, large-area 3D point cloud data. A high-precision inertial measurement unit (IMU) provides the system with high-frequency attitude, angular velocity, and acceleration information. A wheeled odometer collects wheel speed data to provide short-term pose increment information, effectively supplementing the lidar and IMU. An edge computing device performs real-time data processing using SLAM algorithms. An embedded motion control unit runs an operating system to precisely control the chassis motors and transmit data with various subsystems. The software framework is built on the operating system and includes distributed nodes, a publish / subscribe communication model, and an open-source toolkit ecosystem. This achieves lightweight 3D perception capabilities, strong anti-interference performance, and supports fully automatic online repositioning, making it suitable for use in underground infrastructure such as subway tunnels, urban utility tunnels, and large warehousing centers.

The invention relates to the technical field of agricultural plant protection, in particular to a biological control and management method for asparagus diseases and insect pests, which comprises the following steps: S1, soil pretreatment and construction of a beneficial microorganism matrix; s2, pest population dynamic monitoring and natural enemy release; s3, application of the botanical attractant; s4, field application of the biocontrol inoculant; s5, ecological weeding management: in the growth period, controlling the height of worst weeds and keeping low flowering weeds at the same time; s6, harvesting period management: tools are disinfected during harvesting, tender stems are smoothly cut by a special harvesting knife, and residual and broken tender stems are cleaned in time; wherein the steps S1 to S6 form a complete management period and need to be circularly and repeatedly implemented, and the steps S2 to S5 are dynamically executed according to field monitoring conditions. The growth of asparagus root systems is effectively promoted through measures such as a compound microbial agent and ecological weeding management, and adverse effects on asparagus growth are reduced by controlling weeds and plant diseases and insect pests.

This application provides a multimodal input method and device based on the collaboration of a pressure-sensitive pen and a physical keyboard. The method includes: detecting the sensing signal generated by the electromagnetic pen above the screen of a tablet device and determining the hovering distance value of the electromagnetic pen; when the physical keyboard is connected and the hovering distance value is less than a first distance threshold, determining the initial input mode of the current foreground application; acquiring the pressure value received by the tip of the electromagnetic pen, performing analog-to-digital conversion on the pressure value to generate a pressure-sensitive value, and scanning the level changes of each key on the physical keyboard to generate a key scan code; switching the initial input mode according to the pressure-sensitive value and the key scan code, determining the pressure sensitivity level identifier according to the value range of the pressure-sensitive value, combining the modifier key value in the key scan code with the pressure sensitivity level identifier, and searching for the corresponding compound instruction from a preset shortcut key mapping table for input control. This application can maintain operational continuity and significantly improve input efficiency.

This invention discloses a large depth-of-field real-time drift correction method and system based on a programmable point spread function (PSF). This invention achieves wide-range, high-precision drift correction by dynamically switching different PSF modes, solving the problem of the trade-off between axial correction range and accuracy in existing technologies. This invention includes a marker detection module, a dynamic PSF switching module, and a closed-loop control module. It automatically selects the optimal PSF mode based on the real-time detected drift: astigmatic PSF is enabled when |z|≤1 μm, switching to double-helix PSF when 1μm<|z|≤2μm, Bessel PSF when 2μm<|z|≤3μm, and cloverleaf PSF is activated when |z|>3μm. Through adaptive PSF switching, this invention achieves full closed-loop real-time correction within a 6μm axial range, with a drift suppression error ≤2 nm, making it suitable for long-term super-resolution imaging of live cells.

This invention relates to the field of integrated circuits and discloses a mixed-precision in-memory computing circuit, data processing method, and chip. The invention includes: a storage array, an index memory, and a multiply-accumulate calculation circuit. The storage array includes a first data element stored in a first precision format and / or a second data element stored in a second precision format; wherein the bit width of the first precision format is greater than that of the second precision format; the storage locations of the storage array are divided according to the bit width of the second precision format; the first data element occupies multiple consecutive storage locations; the read bit width of the storage array is an integer multiple of the bit width of the first precision format; the index memory stores the position index information of the first data element in the storage array; the multiply-accumulate calculation circuit is used to determine the precision format corresponding to the data read from the storage array based on the position index information, and performs a multiply-accumulate operation corresponding to the precision format, outputting the calculation result. This solves the compatibility problem between mixed-precision data storage and computing circuits.

The present application relates to atomization delivery device technical field, especially in pneumatic control's atomization guide device, including casing, liquid guide device, air pump, controller and injection mixing assembly, the casing is equipped with bottle mouth connection cavity, the bottle mouth connection cavity is used for with the bottle mouth of liquid storage bottle can be detached seal connection;The bottle mouth connection cavity is equipped with one-way air supplement valve, the one-way air supplement valve is communicated with the outside and the inside of the liquid storage bottle, in order to be supplemented to the liquid storage bottle air;The injection mixing assembly has gas inlet, suction inlet and mixing outlet, and includes the gas nozzle, throat and pressure recovery section that are communicated in turn, wherein, the gas inlet is communicated with the gas nozzle, the suction inlet is communicated with the low pressure area of the throat, and the mixing outlet is communicated with the pressure recovery section;Mixed gas-liquid two-phase mixed flow through the mixing outlet enters the liquid guide inlet and is atomized by the atomizing nozzle and is output, realizes the effect that spraying output is more continuous, atomization is more uniform.

The application discloses a kind of based on narrowband internet of things atmospheric methane concentration prediction method, comprising the following steps: collecting methane and environmental data and regular formation multi-source monitoring sequence;Extract concentration change, disturbance coupling and sensing stability form local evolution microstate;Construct fact prediction branch and counterfactual missing report prediction branch to obtain counterfactual missing report influence;Determine prediction closure and closure inertia;Generate closure state and minimum recovery fragment candidate;When fracture triggers, upload closure fracture witness package and generate prediction result and closure update configuration;Write back closure update configuration and update each branch and closure state form prediction closed loop.The application uses the prediction closure method driven by counterfactual missing report influence, realizes atmospheric methane concentration low overhead prediction and recovery, with the advantages of low transmission burden, strong prediction continuity and high adaptability.

This invention belongs to the field of prefabricated building technology and discloses a prefabricated ceiling and its installation method. A supporting component is provided between the keel component and the panel. The supporting component includes a hanger connecting the keel component and a supporting rod for connecting the panel. The panel has a bearing groove formed by bending at least two opposite sides. The bearing groove extends along the edge of the panel and has an open structure design at the corner of the panel to facilitate the lateral sliding or insertion of the supporting rod. This invention provides an independent supporting component composed of hangers and supporting rods between the keel component and the panel, so that the support of the decorative panel no longer depends on the continuous passage of the secondary keel. When the secondary keel path encounters electromechanical pipelines such as fire sprinkler pipes, it can be directly bypassed without on-site cutting; while the panel obtains effective support through adjustable supporting rods.

The application discloses a bronchoscope supply-demand dynamic matching method based on multi-source data fusion, comprising: collecting multi-source heterogeneous data and performing fusion processing to obtain a device feature matrix, a demand feature matrix and an environment feature vector; determining a score calculation strategy according to a comparison result of a historical matching data accumulation amount and a preset threshold, determining a device availability score and a demand urgency score based on the device feature matrix and the demand feature matrix according to the score calculation strategy; constructing a device queue and a demand queue, attaching an initial scene label to each demand and performing identification, and outputting a standardized scene type; outputting an optimal matching scheme through a reinforcement learning intelligent agent based on the device queue, the demand queue, the standardized scene type and the environment feature vector; performing intelligent scheduling based on the optimal matching scheme, updating the queue based on external real-time events, and if both queues are non-empty at the same time, obtaining a new optimal matching scheme, otherwise, keeping a waiting state. The application can improve matching efficiency and accuracy.

The application belongs to the field of solid-state lithium battery materials, and provides a polymer-based solid-state electrolyte film, a preparation method and application thereof, and the application forms a crosslinked shell layer formed by polyvinyl alcohol, polyethylene glycol diglycidyl ether, boric acid and lithium hydroxide monohydrate outside a polyvinylidene fluoride-hexafluoropropylene copolymer core microsphere, and is dry-mixed and hot-pressed into a film with lithium bisfluorosulfonylimide to form a core-shell composite microsphere conduction and support system, so that the film body maintains the processability while taking into account the chain segment movement, structure constraint and residual solvent control, solves the problem that the mechanical strength and ion conduction, the processing fluidity and the electrochemical stability are difficult to be considered, and is suitable for a full solid-state lithium secondary battery.

This application provides a method and system for detecting heavy metal pollution migration in abandoned mining areas. The method involves collecting soil electrical impedance data from the abandoned mining area to the observation area using an intelligent impedance sensor. Based on this data, the impedance change information of each potential pollution unit is determined, and a heavy metal pollution migration model is constructed. Dynamic migration resistance for different potential migration channels is generated based on the pollution migration model. Source similarity is determined based on all isotope ratio information. Time-varying path inversion is performed on the pollution migration model based on all dynamic migration resistances and source similarity to obtain the dynamic migration risk of heavy metals in multiple main migration channels. The detection strategy for heavy metal pollution migration in each main migration channel is adaptively adjusted based on all dynamic migration risks. Using the scheme of this application, detection lag caused by dynamic changes in environmental factors can be avoided.

The application provides a temperature control method and system for an automatic production line of baked paint doors. The method includes generating a three-dimensional thermal field model containing position coordinates, temperature difference values and area ratios by dynamically scanning the temperature distribution data of the door body surface during movement; then constructing a three-layer air duct system with independent adjustment of the top, middle and bottom parts, dynamically adjusting the rotation angle and air flow intensity of the corresponding level deflector to form an air flow coverage mode matching the door body curved surface; when the area ratio of the abnormal area exceeds the standard, adjusting the air door opening, synchronously calculating the compensation air volume increment coefficient to generate a level compensation instruction; finally, adjusting the heat dissipation intensity through the increment coefficient, forming a directional heat dissipation loop in cooperation with the deflector angle correction and static pressure tank vortex suppression device. The technical scheme provided by the application realizes dynamic perception of temperature abnormalities, accurate compensation of multi-level air flow and closed-loop control of over-temperature protection during the curing process of special-shaped door plates, and improves the curing uniformity and quality stability of the paint surface.

The invention discloses a magnetic easy-to-separate Fe3O4-SnO-SiO2 composite catalyst and preparation and application thereof.The composite catalyst is of a core-middle layer-shell layer three-layer core-shell structure, a shell comprises a coating layer, the core comprises a magnetic core, the middle layer comprises an active layer, and the active layer is evenly adsorbed to the surface of the magnetic core; the magnetic core is Fe3O4; the active layer is any one or more than two of SnO, ZrO2 and TiO2; the coating layer is made of SiO2 and wraps the outer side of the active layer. The problems that efficient catalysis, convenient magnetic separation, long-acting circulation stability and precise regulation and control of a product structure cannot be synchronously solved in the prior art are solved. The conversion rate of the catalyst for catalytic synthesis of trimethylolpropane trioleate reaches 94.32%; the friction coefficient of the product is stabilized at 0.09-0.10, the wear volume is reduced by more than 68%, and the magnetic separation recovery rate is 98%.

The utility model discloses a pad face paint coating thickness evenness control device relates to plate processing technical field. The device includes the organism, is provided with the support frame on the organism, is provided with the scraping unit between the support frame and the organism, is provided with the conveyer belt on the organism in the scraping unit, and the V -shaped scraper opening direction is contrary with the conveyer belt moving direction. Vertical adjusting spare is arranged in the inside of support frame. The waste collection spare is arranged in the inside of V -shaped scraper. The device adopts V -shaped scraper and can effectively guide the flow of paint, compared with traditional horizontal plate scraper, reduces the accumulation phenomenon of paint on the scraper, thereby guarantees the uniform coating of paint, improves the coating quality of pad, through the waste collection spare, can collect the extra paint on V -shaped scraper in time, avoids the waste of paint, and also further guarantees the cleaning and normal work of scraper, maintains the stability and continuity of coating process.

The invention relates to a real-time interactive hybrid ocean simulation method and simulation system based on unified spectrum control, and the method comprises the following steps: obtaining environment wind field parameters, and generating a unified ocean wave spectrum; based on the unified sea wave spectrum, generating a JONSWAP spectrum model by adopting fast Fourier transform, and simulating a global wave field by using the JONSWAP spectrum model; and determining the position of an interactive object, dynamically injecting wave particles at the boundary of a local area corresponding to the position based on the unified sea wave spectrum, generating near-field fluctuation, and superposing the near-field fluctuation to a global wave field to form a continuous mixed sea surface. Compared with the prior art, the method has the advantages of uniform spectrum control, efficient parallel computing, high physical consistency, high expandability and the like, and uniform simulation of the large-scale continuous sea surface and the local interaction area is realized.

The method for sensing the temperature of urban solid waste incinerators based on a self-attention hybrid ensemble network belongs to the field of industrial process modeling and intelligent sensing. This method addresses the highly nonlinear, multi-condition variations, and complex physical-chemical reaction mechanisms in the MSWI process. Combining an ensemble learning framework and improved neural network structure, it introduces moving block bootstrap (MBB) sampling based on maximum likelihood estimation (MLE), a self-attention mechanism, and a hybrid ensemble strategy fusing AdaBoost and Bagging to achieve accurate modeling and dynamic prediction of the Fourier transform (FT). This results in good modeling accuracy, generalization ability, and engineering adaptability. Experimental verification under multiple benchmark problems and actual MSWI conditions demonstrates that the proposed FT sensing method exhibits superior performance in both prediction accuracy and robustness, possessing significant engineering application potential and widespread value.

The invention belongs to the technical field of water treatment, and particularly discloses a matrix type separation filler structure which comprises a bearing component fixed in a pool body structure and extending in a second direction perpendicular to a first direction, and a plurality of separation plates arranged in sequence, the bearing component is provided with a gap, the gap is connected with the separating plates in an inserted mode, and each separating plate is provided with a protruding part protruding out of the bearing component. The separating plates and the bearing components are matched with each other to form channels distributed in a matrix mode, and the protruding parts and the gaps are matched to form freedom degrees between the separating plates and reduce brittle sediments attached to the interiors of the channels. The device has the following advantages that the integrity and stability of channel arrangement can be kept under the impact action of water to be treated, and the scattering and damage risks of the separation plates are reduced; brittle sediments in the channel are reduced through the degree of freedom and the shearing effect, and the risk that the channel is blocked due to deposited mud blockage is reduced, so that the separation capacity is favorably maintained, and the operation and maintenance burden is reduced.

This application provides a binocular six-axis low-cumulative-error spatial positioning method and apparatus, applied in the field of positioning and navigation technology. When an anomaly is detected in the spatial motion correlation between vision and inertial at continuous time intervals, it is determined that the current moment is in a state of perception history break. The visual pose constraints at the corresponding moment are isolated from the historical visual constraint set and participate in pose calculation only in an independent local visual constraint set, thereby avoiding the continuous accumulation of abnormal visual constraints in the time dimension and interference with inertial pose updates. In the absence of perception history break, the consistency between the historical visual constraint relationship and the inertial pose change sequence and spatial motion self-consistency data is reviewed, and inconsistent visual constraint relationships are dynamically eliminated. This allows the effectiveness of visual constraints in pose fusion to be adaptively adjusted over time, suppressing the amplification process of inertial cumulative error and meeting the requirement of maintaining high-precision positioning under complex environments and long-term operating conditions.

The present application relates to the technical field of data prediction, and discloses a coal calorific value high-precision prediction method based on machine learning; the method comprises the following steps: obtaining coal quality detection data and performing windowing processing to form a coal calorific value sequence and a multi-source coal quality component sequence; a disturbance embedding vector group is constructed according to adjacent measurement value changes; statistical features and dominant amplitudes of coal quality component variables are extracted, a signal-to-noise factor is constructed, and a selection weight is obtained through mapping to generate a variable-level coal quality feature vector group; the disturbance embedding vector group and the variable-level coal quality feature vector group are combined in time sequence to form a coal quality correlation modeling set, and a sparse correlation structure field is constructed based on a training set; a comprehensive state representation is obtained through correlation propagation and steady-state consistency constraints; a test set is input into the mechanism to obtain a coal calorific value prediction result sequence; the method can strengthen disturbance expression, improve feature fusion quality, and maintain prediction structure stability, and a coal calorific value high-precision prediction result is obtained.

The application discloses an electromagnetic point reading pen positioning method based on image recognition, and comprises the following steps: S1, collecting a textbook page image, combining an improved SuperPoint model and a time sequence processing unit to complete feature extraction, alignment, difference calculation and learnable parameter optimization of a key point set and a descriptor vector; S2, generating a layout template; S3, extracting and screening the key point set to generate current frame feature data containing two-dimensional coordinates, confidence and a normalized descriptor; S4, generating visual registration parameters; S5, combining the visual registration result to compare and update initial electromagnetic prior registration parameters, and outputting effective registration parameters of a current operation cycle; and S6, generating a positioning coordinate sequence and updating visual registration prior parameters. The application can realize high-precision and low-drift page positioning under different paper materials, illumination conditions and long-time use conditions, and is suitable for intelligent point reading, interactive teaching and high-precision paper surface interaction scenes.