35results about How to "Implement automatic classification" patented technology

According to the invention, the internal association relationship between the fault working condition attribute and the fault feature is mined, and the fault information fusion-based power system transient protection method is provided. The fault information fusion method adopts a Kalman filtering algorithm and an improved Kalman filtering algorithm, or adopts a particle filtering algorithm or an improved particle filtering algorithm. And the fault can be reflected more accurately by fusing the standard fault characteristics of the fault working condition attributes. According to the power system transient protection method based on the fault working condition attribute, the adverse effect of the fault initial phase angle and the transition resistance on protection is overcome, and the transient protection reliability is improved.

The present invention proposes a medical record data processing method and system based on multi-agents, the method comprising: collecting medical record data in the hospital information system and preprocessing; designing multiple agents, using a multi-agent reinforcement learning algorithm to train the agents, autonomously learning the optimal strategy for classifying and processing medical record data through mutual cooperation and competition between the agents, introducing an attention mechanism to construct an adaptive pre-training model based on a bidirectional long short-term memory network to intelligently extract medical record data and extract key information; using a generative adversarial network to enhance and repair medical record data and generate enhanced medical record data samples; real-time monitoring of the updated knowledge graph, real-time optimization of the knowledge graph according to the monitoring results, and entry and dynamic update of medical record data. The present invention provides an efficient, accurate and flexible medical record data processing method and system through the combination of multiple cutting-edge artificial intelligence technologies.

The invention discloses an automatic garbage classification device for a smart city and a using method thereof, relates to the technical field of garbage classification, and solves the problems that in the existing garbage throwing and classification process, classified collection of a garbage truck is inconvenient, solid-liquid separation of garbage cannot be achieved, electric quantity supplementation of the garbage can is inconvenient, and environmental protection is not facilitated. The automatic garbage classification device for the smart city and the using method of the automatic garbage classification device for the smart city comprise a mounting and conveying mechanism, and two classification and storage mechanisms are mounted on the inner side of the mounting and conveying mechanism; and the classified storage mechanism comprises a classified storage box, a movable baffle, a fan box, a liquid injection plate, a disinfectant spraying head, a garbage guide inclined plate, a garbage temporary storage seat, a garbage compression plate and a hydraulic rod. According to the garbage disposal device, garbage which is thrown in a classified mode is automatically compressed and subjected to solid-liquid separation, garbage transfer and disposal are facilitated, cleanliness of a throwing point can be kept, and electric energy supplementation is facilitated by adjusting the angle of the solar cell panel.

The present application discloses a method, apparatus, device and computer-readable storage medium for application classification, which belongs to the field of terminal technology. The method includes: obtaining an application package of an application; based on the application package, obtaining a registry file of the application; based on the registry file, generating target information, the target information is used to indicate the category of the application; according to the target information, determining the category of the application. The method realizes automatic classification of applications, improves the classification efficiency of applications, simplifies the operation process of user application classification, and optimizes the user experience. In addition, for any application that includes a registry file, the solution can realize automatic classification of the application, and has a wide range of applications.

The utility model relates to the technical field of automatic garbage classification boxes, in particular to an automatic garbage classification box which comprises a shell, a funnel is embedded in the upper end of the shell, the edge of the funnel and a support of the shell are assembled through screws, two sets of garbage bag breaking knife driving mechanisms which are symmetrically distributed are arranged in the shell respectively, and the two sets of garbage bag breaking knife driving mechanisms are arranged in the shell. Each garbage bag breaking knife driving mechanism comprises two first motors which are longitudinally and symmetrically distributed and a single second motor which is transversely distributed, the outer wall surfaces of the first motors and the outer wall surfaces of the second motors are fixedly assembled with an inner support of the shell through screws, and first rotating shafts used for driving are arranged in the first motors. Compared with an existing intelligent garbage recycling bin, the intelligent garbage recycling bin has the advantage that people only need to throw garbage into one recycling opening, so that garbage classification is achieved. And corresponding operation is not needed, and the operation method is the same as the operation method of throwing the garbage into a common garbage can.

This invention discloses a Yangtze River waterway classification method based on ship feature clustering, comprising: dividing the Yangtze River waterway into multiple segments using an angle bisector method; assigning geographical semantic knowledge such as ports, prefecture-level cities, and provincial-level administrative regions to each segment using overlay analysis; calculating the navigation time of each type of ship within a square grid by dividing the grid, and calculating static traffic characteristics using a summation-based waterway mapping method; calculating relatively discrete traffic characteristics such as speed, acceleration, and turning rate using the mean method, and mapping them to waterway segments using the maximum value method; calculating flow characteristics using a summation method; selecting traffic characteristics with appropriate similarity based on hierarchical clustering analysis; and classifying the Yangtze River waterway using a combination of K-means clustering and sliding window methods. This invention can automatically classify waterway segments in the Yangtze River waterway based on ship traffic characteristics.

The utility model discloses a visual induction garbage classification can teaching aid, which comprises four can bodies arranged on a bottom plate, a first circuit board arranged at the front part of a can cover, a camera electrically connected with the first circuit board, a second circuit board arranged below the first circuit board, the first circuit board of the camera connected with the second circuit board through a lead, and a master control device arranged on the second circuit board. Compared with the prior art, the garbage classification system has the advantages that the automatic classification of garbage is realized through the integrated visual processing algorithm function of the camera and the main control device, and the classification accuracy and efficiency are improved; due to the transparent can body structure, a learner can visually see the classification condition of garbage; the identification stickers provide visual classification guidance information; the whole design structure is compact, functions are complete, and the requirement for garbage classification education is met.

The invention discloses a sample imbalance data processing diagnosis system and method, the system comprises a data import module, a sample classification module, a sample number averaging module, a sample balance module and a data analysis module, the data import module is connected with the sample classification module, the sample classification module is connected with the sample number averaging module, and the sample number averaging module is connected with the sample balance module. The sample number averaging module is connected with a sample balance module, and the sample balance module is connected with a data analysis module; according to the invention, through the use of the sample classification module, automatic classification of data is realized, and errors during group-by-group import are prevented; meanwhile, through the cooperation between the sample number averaging module and the sample balancing module, better data balancing is realized, and offset during model establishment is avoided; meanwhile, through cooperation between the data analysis module and the data prediction module, a data model can be generated on the basis of data analysis, and the application range of the system is widened.

This abstract discloses a waste collection box for wooden toy processing, belonging to the technical field of woodworking machinery accessories. The collection box includes a box body, a pull-out drawer that can be inserted into the box body, and a waste inlet at the top of the box body. The lower end of the waste inlet is connected to a partitioned waste inlet groove. The pull-out drawer has a partition plate corresponding to the partitioned waste inlet groove. A rotating plate is rotatably connected to the outer wall of the pull-out drawer via a connecting platform and an inner shaft. A torsion spring is sleeved on the inner shaft. A side platform and a locking pin are fixed on the rotating plate. The locking pin cooperates with a positioning ring fixed inside the box body to form a locking structure that unlocks upon pressing and automatically resets. This utility model not only achieves automatic waste sorting at the source, facilitating recycling, but also effectively solves the problems of drawer loosening and waste leakage caused by processing vibration through a reliable locking structure. It features a stable structure and convenient use.

The invention discloses a rescue equipment access automation system and a rail rescue vehicle, and the system comprises an operation environment monitoring unit which is used for monitoring the environment information and the operation state information of rescue equipment; the equipment access unit is used for receiving the rescue information and accessing the rescue equipment according to the rescue information; the loading and unloading unit is used for loading and unloading rescue equipment; the central control unit is used for acquiring the environment information and the operation state information, receiving the rescue information, issuing an equipment access instruction to the equipment access unit to access the rescue equipment, and establishing a machine account in real time; and after the equipment access unit takes out the rescue equipment, the central control unit sends an unloading instruction to the loading and unloading unit to unload the rescue equipment, and after the rescue equipment is used, the central control unit sends a loading instruction to the loading and unloading unit to load the rescue equipment. Automatic storing, taking, loading and unloading of rescue equipment are achieved, and the safety of personnel and properties is improved.

This invention discloses a method, apparatus, and device for field extraction based on multi-task deep learning. The method includes: acquiring remote sensing time-series images of the phenological stages of agricultural crops within a region to be identified; inputting the remote sensing time-series images of the phenological stages of agricultural crops within the region to be identified into a trained farmland field extraction framework for prediction, thereby obtaining farmland field identification results; wherein, the farmland field extraction framework is trained based on a remote sensing time-series image training set, which is a dataset within the study area after data preprocessing. This invention solves the problems of poor accuracy and low efficiency in field identification.

The invention relates to the technical field of garbage classification equipment, in particular to an intelligent garbage classification and compression device and a working method thereof. The device comprises a box body, a garbage throwing opening outside the box body, a garbage bag conveying track at the garbage throwing opening, a bag dumping device in the box body, a dispersing device, an intelligent speed control device, a sorting device, an intelligent identification camera on the left side of the sorting device, and four garbage classification areas on the lower part of the box body, wherein the dispersing device, the intelligent speed control device and the sorting device are arranged below the bag dumping device in the box body; the compression device is arranged below the sorting device; garbage is fully separated from garbage bags through the bag dumping device, accurate sorting is achieved through the sorting device, then efficient compression is conducted through the compression device, efficient and accurate garbage classification is achieved, environmental pollution is reduced, the resource recycling rate is increased, the labor cost is reduced, and the space utilization rate is increased, and the device is suitable for various places and has wide application prospects. Meanwhile, the environmental awareness of the public is also improved.

The invention discloses a circuit board code spraying device for circuit board production, which comprises a control unit, a feeding conveying unit, a first discharging conveying unit, a second discharging conveying unit, a turntable, a turntable driving unit and a first code spraying unit, and is characterized in that four material moving conveying units are mounted at the turntable, and the turntable is provided with a feeding position, a code spraying position, a detection position and a discharging position; the feeding conveying unit faces the feeding position, the first discharging conveying unit faces the detection position, the second discharging conveying unit faces the discharging position, and the first code spraying unit can conduct code spraying on the circuit board at the code spraying position. According to the circuit board code spraying device, automatic code spraying can be achieved, double-face code spraying is achieved, the production efficiency is greatly improved, manual intervention is reduced, and the production cost is reduced. And after code spraying is finished, detection can be realized, so that the accuracy, integrity and definition of code spraying information are ensured, and the product quality requirement is met. And automatic classification of qualified products and unqualified products can be realized.

The embodiment of the present invention discloses a method and device for digitizing paper documents. It includes: processing the content of paper documents to be classified, extracting key information of the paper documents to be classified; determining standard information matching the key information in the document type information library, and determining the document type to which the standard information belongs as the document type of the paper documents to be classified; generating structured information of the paper documents to be classified based on the structured format corresponding to the document type and the content of the paper documents to be classified; and associating and storing the paper documents to be classified, the document type of the paper documents to be classified, and the structured information. It can realize automatic classification and automatic document recording of documents, replace manual operations, have higher accuracy and processing efficiency, and make document data more specific and detailed.

The invention belongs to the field of high-voltage circuit breaker fault diagnosis, and discloses a high-voltage circuit breaker bolt loosening fault diagnosis method and related equipment. According to the method, a voiceprint prototype is finally formed in an embedding space through the steps of extracting the occurrence moment and the termination moment of a bolt loosening sound signal, constructing an all-pole model, solving an all-pole filter coefficient, calculating a group delay function, performing discrete cosine transform to form a frequency spectrum enhanced voiceprint feature and the like in sequence. The attribution probability of the voiceprint to be diagnosed is determined by calculating the distance between the voiceprint to be diagnosed and the voiceprint prototype, so that the bolt loosening fault is accurately diagnosed; the method does not depend on a huge sample data set, but represents different bolt loosening states based on the voiceprint characteristics of the sound signals sent by breaking of the circuit breaker, the formant of the sound signal frequency spectrum is enhanced, the representation effect of the bolt loosening of the high-voltage circuit breaker is improved, and the reliability of the high-voltage circuit breaker is improved. And the bolt loosening fault diagnosis of the high-voltage circuit breaker under the condition of insufficient actual samples is realized.

The application discloses a kind of based on health-care product packaging bottle processing's hierarchical conveying device and method, it is related to the technical field of packaging bottle conveying detection.The present application includes the big and small packaging bottle being arranged on conveying table, further includes: conveying unit, main conveying belt is arranged in it, and sorting assembly for sorting big and small packaging bottle is arranged on main conveying belt;Conveying table is provided with preferred unit;Preferred unit includes appearance detection assembly, air tightness detection assembly and rejection assembly.The advantages are that: the present application can be according to the volume of packaging bottle and be divided into corresponding sub-conveying belt and be conveyed, can realize the automatic classification and independent conveying of big and small packaging bottle, and appearance defect and air tightness detection can be carried out to packaging bottle in conveying process, and the substandard product in packaging bottle is detected in real time, and the substandard product can be rejected from sub-conveying belt in real time, avoid substandard product mixed in qualified bottle and affect the final product effect, conveying efficiency is higher, and functionality is stronger.

The invention relates to the technical field of automation equipment, in particular to multifunctional integrated equipment used in a front reduction piston production line, the multifunctional integrated equipment comprises an equipment body and a front reduction piston, and the equipment body comprises a feeding mechanism, a transfer measuring mechanism and a marking detection mechanism which are sequentially and coherently arranged; the feeding mechanism is used for providing corresponding front reduction pistons to a production line, the transfer measuring mechanism is used for transferring the front reduction pistons from the feeding mechanism to the marking detection mechanism and measuring the diameters of the front reduction pistons in the transfer process, and the marking detection mechanism is used for marking and detecting the front reduction pistons. Qualified and unqualified products are classified and output; according to the automatic production line, feeding, transferring measurement and marking detection are integrated, automation, high efficiency and intellectualization in the production process of the front reduction piston are achieved, and the production efficiency and the product quality are greatly improved.

The present invention discloses a high-precision analysis system for invoice amounts based on OCR, including a system terminal and a server; the system terminal provides users with an image scanner for reading the invoices required for analysis; the server stores a pre-trained network model and a complete set of system source codes; the network model includes image classification, OCR text recognition CRNN unit and image feature matching unit; the image classification adopts the MobileNet V3 classification network; the image feature matching unit adopts the SIFT algorithm to perform feature matching, positioning and extraction; the OCR text recognition CRNN unit identifies the required information; the complete set of system source codes realizes the integration of the network model and the analysis visualization interface. The image processing module of the present invention realizes the automatic classification of multiple bills by combining the use of the MobileNet V3 classification network and the SIFT algorithm for feature matching, positioning and extraction, and performs targeted positioning of the modules that need to be identified, thereby reducing unnecessary processes, saving time, and improving efficiency and recognition accuracy.

The present application relates to a method for automatically generating wall, column and beam components in Revit based on 3D scanning point cloud data. The method comprises: S1, point cloud data acquisition and preprocessing, denoising, simplifying and aligning the original point cloud; S2, point cloud feature extraction and component classification, point cloud segmentation is performed by region growing algorithm, component type identification is performed by deep learning model and attribute parameters are given; S3, Revit component mapping and model generation, mapping rules are set through Revit plug-in, corresponding building components are automatically created in Revit and parameters are set; S4, model verification and optimization, the deviation between the model and the point cloud is automatically calculated and manual correction and lightweight processing are performed. The present application realizes the automatic conversion of point cloud data to Revit model, the modeling efficiency is improved by more than 80%, the model accuracy can reach ±2cm, and can be widely applied in old building reconstruction and existing building digitization fields.

The invention relates to a full-automatic drying production line for wood tray processing, and relates to the technical field of wood tray production, through cooperation of a box body mechanism and a first transmission belt, automatic feeding and discharging are achieved, manual operation of workers is not needed, and the labor amount of the workers is reduced; and through cooperation of the conveying mechanism and the detection mechanism, the wood trays with the rivets extending out are conveyed out from a third conveying belt, the wood trays without the rivets extending out are conveyed out from a second conveying belt, it is achieved that whether the rivets extend out of the upper surfaces of the wood trays or not is automatically classified, and the work efficiency is improved. In the process that the driving mechanism drives a U-shaped plate in the detection mechanism to lift up and down, a baffle is driven to move up and down, opening and closing of a box body outlet are achieved, the wood trays can be output in the box body opening and closing process, and the quality of finished wood trays is improved. And the situation that heat in the box body is quickly dissipated after the outlet is opened for a long time is avoided.

The utility model discloses a hardware stamping part processing discharge device relates to hardware stamping part discharge device technical field, include: support, the lateral wall fixed mounting of support has distribution box, the top surface rotationally connected with first transmission belt of support, one side rotationally connected with second transmission belt of first transmission belt, and the lateral wall of first transmission belt is provided with the fender, and the lateral wall of fender is provided with visual screening machine, overturns spare, overturns spare and is arranged on fender, and is used to overturn the hardware stamping part of needing detection, shunt spare, shunt spare and is arranged on fender, and is used to shunt after the hardware stamping part of detection, be equipped with overturning spare, can carry out comprehensive detection to hardware stamping part, solved the problem that traditional equipment can not detect hardware stamping part bottom surface. The cooperation of electromagnet and drive motor no.

The invention relates to an image recognition and classification method and system based on an SVM (Support Vector Machine) and easyocr. The method comprises the following steps: carrying out supervised training on an image sample through the SVM; generating classified key elements and an image ROI (Region of Interest) according to the features of the image; and carrying out classification by using a support vector machine (SVM), carrying out OCR identification again when the confidence is lower than a confidence threshold, and correcting a classification result according to an OCR identification result. According to the method, recognition can be carried out while classification is carried out, correction of an image classification result and online supervised learning are realized through OCR, and the accuracy of machine learning image classification is improved; according to image characteristics, classification and identification of newly added images are realized through a real-time local parameter configuration mode.

The invention provides an image classification method based on a residual neural network, and the method comprises the following steps: collecting high-resolution satellite remote sensing image data, and guaranteeing the coverage of a plurality of ground feature types; preprocessing the image, namely adjusting the image to be smaller in size, and performing pixel value normalization and data enhancement; dividing the processed data set into a training set, a verification set and a test set; a model architecture based on a residual neural network is adopted, a plurality of residual blocks are used, and input is directly added to output through jump connection so as to relieve the gradient disappearance problem; a converter module is connected behind the residual neural network, and a self-attention mechanism is utilized to process the output of a convolutional layer so as to capture global features; a cross entropy loss function and an Adam optimizer are used for model compiling, and an early stop strategy is adopted in the training process to prevent overfitting; and performing performance evaluation on the trained model by using the test set, calculating the accuracy rate, the recall rate and the F1-score, and performing result visualization to optimize the classification effect.

The present invention belongs to the technical field of battery production, and in particular, relates to a fully automatic weld spot detection bending machine device, the device comprising a feeding mechanism, a feeding mechanism, a station rotating disk, and a tab leveling mechanism, a weld spot detection mechanism, a bending mechanism, and a control component arranged along the circumference of the station rotating disk; the feeding mechanism is used to convey the battery cell to be processed and perform two corrections on the battery cell; the station rotating disk is driven to rotate by a motor to realize the transfer of the battery cell between various stations; the tab leveling mechanism is used to perform flattening processing on the tab; the weld spot detection mechanism is used to detect the weld spot between the battery cell and the tab to determine whether the weld spot is qualified; the bending mechanism is used to perform bending processing on the battery cell protection plate on the tab. The fully automatic weld spot detection bending machine device provided by the embodiment of the present invention can realize automatic inspection of the weld spot of the battery cell and bending of the battery cell protection plate, without manual operation, with a high degree of automation, which can significantly improve production efficiency.

The invention relates to the technical field of computer vision and artificial intelligence, and particularly discloses an emotion recognition and analysis system for learning pictures. The system comprises a modal data acquisition module, a feature automatic learning module, an emotion classification and recognition module, an emotion intensity analysis module, a feedback and optimization mechanism and a visualization and interaction interface. The system can adapt to complex and changeable emotion expression scenes.

The invention relates to the technical field of agricultural product classification and transportation, and discloses a classification and transportation device for primary agricultural product purchasing, which comprises a base, and a classification assembly is arranged on the rear side of the top end of the base and is used for classifying primary agricultural products according to sizes; a conveying assembly is arranged at the top end of the base and used for conveying the classified agricultural products. A driving assembly is arranged outside the conveying assembly and used for starting the conveying assembly and the vibration assembly. A self-adaptive assembly is arranged outside the driving assembly and is used for adjusting the adjusting belt pulley; a vibration assembly is arranged outside the classification assembly and used for vibrating the classification net to improve the classification efficiency. Through the design of different meshes in the classification net, the cam drives the baffle to move, the baffle drives the connecting rod to move, the push block drives the classification net to vibrate, and therefore agricultural products of different sizes can be rapidly and accurately classified into different discharging boxes, and the classification efficiency is improved.

The utility model relates to the technical field of logistics conveying, in particular to an automatic conveying line capable of freely adjusting direction and speed, which comprises a support, a first conveying line, a second conveying line and a third conveying line, a transparent plate used for placing fruits is fixedly mounted on the support, and a colorimeter used for corresponding to the transparent plate and testing the fruits is arranged on the support. A controller matched with the colorimeter is arranged on the support, and a motor is fixedly installed on the support. According to the fruit sorting device, the second conveying line and the third conveying line are arranged on the support, the second conveying line and the third conveying line can sort mature or immature fruits, and automatic sorting can be achieved when the fruits are conveyed; the intercepting plate can correspond to the second conveying line or the third conveying line during rotation through driving of the motor, then fruits can be intercepted through deflection of the connecting rod, the fruits can fall into a designated collecting frame according to a designated path, and therefore the fruit conveying efficiency is improved.

The invention provides a method and device for grouping the occurrence of structural surfaces based on a sparrow algorithm, and relates to the technical field of rock mass structural surface grouping. The method and device include converting a plurality of structural surface samples into normal vector samples of a plurality of spatial units in sequence; initializing a sparrow population based on the current number of clusters, updating the spatial position of the initial sparrow population, calculating the fitness value of the updated sparrow population, and obtaining the optimal sparrow population corresponding to the minimum fitness value; clustering the normal vector samples using the optimal sparrow population, and calculating the validity index of all clustered structural surface samples; and taking the number of clusters corresponding to the maximum value of the validity index and the clustering result as the final grouping. The invention is used to solve the technical problem that the existing occurrence grouping method is highly subjective and cannot accurately and quantitatively give objective grouping results.

This application proposes an image classification method, apparatus, and device. The method includes: identifying whether an image to be processed is a beautified image using a pre-trained face detection model and a beautification recognition model; classifying the image to be processed using a pre-trained multi-class classification model to obtain the probability of the image belonging to each image category; and identifying whether the image to be processed contains an image of a target person using a pre-trained person classification model. This application integrates a beautification recognition model for identifying beautified images, a multi-class classification model for classifying multiple image categories, a person classification model for identifying whether an image contains a target person, and so on. By using these multiple models to automatically classify the image to be processed, the method offers strong real-time performance, enabling automatic classification of a large number of images and improving the efficiency of image data structured processing.

The invention relates to the technical field of visual detection, in particular to aluminum alloy workpiece sealing ring installation visual detection equipment and method.The aluminum alloy workpiece sealing ring installation visual detection equipment comprises a base, a supporting frame, a conveying line, a detection assembly and a classification assembly, the supporting frame is fixedly connected with the base and located at the top of the base, and the conveying line is rotationally arranged on one side of the supporting frame; the detection assembly is arranged on one side of the conveying line and used for photographing to monitor the mounting condition of the sealing ring; the sorting assembly comprises a driver, a lifter, a poke rod, a first auxiliary line and a second auxiliary line, the first auxiliary line and the second auxiliary line are arranged on the two sides of the conveying line, the driver is arranged above the conveying line in a sliding mode, the lifter is connected with the output end of the driver, and the poke rod is connected with the output end of the lifter. Therefore, the workpiece sealing rings can be automatically detected and classified, and the working efficiency is improved.