15results about How to "Avoid misidentification" patented technology

The invention provides a coal mine rock burst prevention method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring first monitoring data of a coal seam roof rock stratum, wherein the first monitoring data at least comprises a fracture event and micro-fracture distribution density of the coal seam roof rock stratum; determining that the rock burst risk exists in the coal seam roof rock stratum in response to the fracture event and the micro-fracture distribution density meeting the risk identification condition; at least one time of pressure relief treatment is conducted on the coal seam roof rock stratum, and different pressure relief agents are used in the at least one time of pressure relief treatment process; and second monitoring data of the coal seam roof rock stratum after pressure relief processing are obtained, and when the second monitoring data do not meet the risk identification condition, it is determined that rock burst risk prevention and control are completed. Therefore, according to the scheme, combined monitoring of various data can be achieved so that the rock burst risk can be accurately recognized, roof pressure relief is achieved through cooperative prevention and treatment of at least one time of pressure relief treatment, and therefore the pressure relief effect is improved.

The invention discloses an unmanned aerial vehicle water-air dual-medium adaptive communication optimization method and related equipment. The method comprises the following steps: acquiring unmanned aerial vehicle environment sensing information; determining the current communication medium state of the unmanned aerial vehicle according to the unmanned aerial vehicle environment sensing information; the communication medium state comprises an air state, an underwater state and a water-air interface crossing state; generating a target communication strategy according to the current communication medium state of the unmanned aerial vehicle, and controlling the unmanned aerial vehicle to execute the target communication strategy; the communication strategies comprise an air communication strategy, an underwater communication strategy and a water-air dual-medium communication strategy; and dynamically monitoring the communication link performance index of the unmanned aerial vehicle, and dynamically optimizing the target communication strategy in combination with the environment change information and the communication link performance index. The technical problem that the communication performance of the unmanned aerial vehicle on the water-air interface is sharply reduced can be effectively solved, smooth transition and high-reliability maintenance of the communication link in the double-medium environment are achieved, and the method can be widely applied to the technical field of unmanned aerial vehicle communication.

This invention provides an automatic fiber extraction method, a training method for a fiber segmentation model, and an electronic device. The automatic fiber extraction method includes: segmenting a patient's medical image using a fiber segmentation model to obtain a segmentation result; wherein the fiber segmentation model is a pre-trained deep learning model for extracting slender structures; and performing connected component analysis on the segmentation result to extract the fiber region. This invention pre-trains a fiber segmentation model, which is particularly suitable for extracting slender structures in three-dimensional medical images, improving the accuracy and efficiency of fiber segmentation. After obtaining the fiber mask through segmentation, connected component analysis is performed to further accurately screen out the fiber region, eliminating interference from artificial filling materials, blood vessels, and other noise, thus more accurately determining the fiber region.

The application discloses a notebook shell identification stamping forming device and belongs to the technical field of notebook shell production and processing. The device comprises an upper die assembly, a lower die assembly, a first identification assembly, a second identification assembly and a rib member. The first identification assembly is arranged on the upper die assembly. The second identification assembly is arranged on the lower die assembly. The first identification assembly comprises one or more first identification blocks. The rib member is provided with one or more. The second identification assembly comprises one or more second identification blocks. One end of the first identification block protrudes from one side of the upper die assembly and the lower die assembly. The rib member is arranged on one side of the second identification assembly facing the upper die assembly, and the rib member is arranged in a circumferential direction along the edge of the second identification block and the first identification block. The rib member protrudes in the direction of the upper die assembly. The above technical scheme has the advantages of high processing efficiency and avoidance of the formation of an R corner at the top edge of the identification area on the shell.

This invention relates to the field of communication technology, specifically a communication data security analysis and processing method, system, and storage medium. The method includes: recording communication data for various IoT scenarios based on edge node monitoring; performing gradient aggregation on the edge node data and filtering target communication subsets for collaborative operation of edge nodes; extracting abnormal communication data under time-delay collaboration based on the logical coordination and temporal continuity of the target communication subsets, combined with the indirect access path composed of edge nodes and regional nodes; transforming the scenario label, node location, and time period of the abnormal communication data into constraints based on the abnormal time and abnormal response intensity associated with the abnormal communication data, and solving for risk collaboration factors when data is abnormal; monitoring scenarios where risk collaboration factors occur, and optimizing the blocking of indirect access paths when new risk collaboration factors are detected. This improves the accuracy and efficiency of communication data risk analysis.

The invention relates to the technical field of image recognition, and provides a license plate recognition method based on video stream deep learning, and the method is characterized in that the method comprises the steps: obtaining video stream data of a monitoring camera, carrying out the frame extraction processing, and obtaining a frame sequence image; preprocessing the frame sequence image, and detecting a license plate area by using a license plate detection model; performing character recognition on the detected license plate area image to obtain a single-frame license plate recognition result; and carrying out preferential selection on the plurality of single-frame license plate recognition results corresponding to the frame sequence image to obtain a final license plate recognition result. According to the method, a complete technical framework integrating image enhancement, deep learning detection and recognition and multi-frame result probabilistic voting preferential selection is constructed, so that real-time, high-accuracy and high-robustness automatic recognition and statistical analysis of license plate information in a video stream are realized.

This invention relates to a method for detecting violations by personnel at conveyor belt stations based on an improved S2ANet and trajectory tracking. The method includes acquiring video and segmenting it into images frame by frame; inputting the images into the S2ANet-CBAM algorithm for conveyor belt target detection to obtain conveyor belt data; inputting the images into the YOLOv5 algorithm for worker target detection to obtain worker data; determining whether the conveyor belt is horizontal by comparing the conveyor belt data and worker data; using a Kalman filter to predict the position information of the worker and conveyor belt in the next frame; and using the Hungarian association algorithm to match and track the trajectories of the worker and conveyor belt. Finally, trajectory correction is performed, and the worker's trajectory and the conveyor belt trajectory are drawn, and the existence of violations is determined. This invention solves the problem of overlapping horizontal target boxes between the conveyor belt and the person in industrial applications due to the large size of the conveyor belt target, avoiding trajectory mismatch problems caused by target occlusion and errors caused by camera shake.

The invention discloses a method for adjusting a vehicle dynamic control function based on a road condition and electronic equipment, which are suitable for an ESC system, and comprise the following steps: introducing pothole bad road identification in a vehicle dynamic control function activation condition; acquiring a basic threshold value of a vehicle dynamic control function under the current vehicle speed / current vehicle steering wheel angle, and setting a pothole and bad road identification threshold based on the basic threshold value; in the pothole and bad road recognition process, after wheels, a wheel speed sensor and an acceleration sensor arranged in an ESC system are synchronously oscillated, oscillation signals sent by the wheel speed sensor and the acceleration sensor are obtained, and the oscillation amplitude and the oscillation period of the oscillation signals are judged step by step through threshold values. Pothole and bad road recognition is introduced into the vehicle dynamic control function activation condition of the ESC system, so that the ESC system not only can recognize the driving road condition, but also has independent control logic for the vehicle dynamic control function under different road conditions, and the activation modes of the vehicle dynamic control function in the ESC system are increased.

This invention relates to the field of control system data processing technology, and in particular to an intelligent cleaning system and its working method that employs a robotic arm for cleaning and drying. The system includes a visual data acquisition module that acquires raw image data; an environmental adaptation processing module that outputs an optimized image matrix; a feature recognition module that extracts part contour and position features from the optimized image matrix and outputs coordinate and posture information; a control decision module that fuses the feature information with preset cleaning parameters to generate robotic arm motion commands; and a robotic arm execution module that drives the spray gun to complete the cleaning action and feeds back the position data acquired by the joint encoder to the feature recognition module to form a closed-loop control. This invention compensates for low-light conditions and suppresses stain noise through environmental adaptation processing, enhances robustness through feature recognition combined with a confidence mechanism, and corrects recognition deviations through feedback loops, ultimately achieving accurate detection of part positions and complete cleaning, thus solving the problems of missed cleaning and uneven cleaning.

The utility model discloses an intelligent identification sound and light guide shared shelf device adopts lamp area, including cabinet, layer board, baffle, pilot lamp, RFID read-write ware, camera, touch -control screen, loudspeaker, electronic lock and base etc.

The application discloses an obstacle vehicle identification method, device and equipment and a storage medium, and comprises the following steps: determining a target scene category of a vehicle driving scene according to a scene image and radar detection information of the vehicle driving scene; determining scene radar clutter according to the target scene category, and determining target radar echoes corresponding to obstacle vehicles in the vehicle driving scene according to the scene radar clutter and the radar detection information; and determining vehicle position information of the obstacle vehicles in the vehicle driving scene according to the target radar echoes. The position information of the obstacle vehicles can be accurately obtained according to the target radar echoes, the misidentification of the scene radar clutter is avoided, and the acquisition efficiency of the vehicle position information of the obstacle vehicles is improved.

The application discloses an in-warehouse article identification method, device, equipment and storage medium. The method comprises the following steps: acquiring a plurality of first identification image information of an in-warehouse article and first identification data information of an article collected by an in-warehouse RFID sensor; determining article identification data according to the first identification image information and the first identification data information; determining first article identification data through the first identification data information; determining second article identification data through the first identification image information; and taking the intersection of the first article identification data and the second article identification data as the article identification data. The application can improve the efficiency of in-warehouse article identification, achieve the goal of accurate identification and rapid identification, and effectively prevent the problem of article identification error.

The invention discloses an intelligent bag taking method and system based on target recognition analysis, and relates to the technical field of target recognition. The method comprises the following steps of bag taking interference analysis, bag taking identification analysis and bag taking decision feedback. According to the method, the bag taking interference analysis result is obtained based on the bag taking identification interference parameters so as to judge whether to carry out image dynamic acquisition adjustment or not, if yes, bag taking dynamic identification analysis is carried out after the image dynamic acquisition adjustment is carried out, and if not, bag taking dynamic identification analysis is directly carried out; recognition errors caused by ambient light changes or other factors are effectively avoided, recognition of the bag taking action is more accurate, whether a bag taking decision feedback mechanism is triggered or not is judged after bag taking dynamic recognition analysis is conducted, if yes, bag taking decision feedback is executed, and if not, image dynamic recognition optimization is executed, so that the bag taking action is more accurate. The reliability of the automatic bag taking machine in actual operation is effectively improved, and then recognition of the bag taking process of the automatic bag taking machine is more accurately carried out.

The invention relates to the technical field of laser measurement, in particular to a laser center reference automatic adjusting system and method with a center detector, and the method comprises the steps: taking a structural member which is in rigid connection with a turbine shafting as a calibration object, and obtaining the laser image information of each calibration object in a laser center alignment shafting; according to the laser image information of each calibration object, calculating the radial deviation and the axial deviation angle of each calibration object, and according to the deviation direction of the calibration object, constructing a deviation distribution diagram of a full-axis section; comparing the deviation distribution diagrams under different time sequences, and outputting a time sequence deviation sequence according to the deviation peak value and the accumulated deviation value corresponding to each time period; determining correction time sequence information of each shaft section in combination with a scene factor of the time sequence deviation sequence; and calculating the laser center adjustment amount of each shaft section to obtain the drift compensation sequence of each shaft section. The scene adaptability and efficiency of drift compensation are realized.