22 results about "False rejection rate" patented technology

The invention discloses a drainage pipeline defect detection system and method based on multi-scale feature fusion and occlusion perception, and the system comprises a data set construction module which is used for constructing a drainage pipeline data set covering multi-defect, multi-scale and multi-occlusion scenes; the model training module is based on establishment of a defect collaborative detection model, and a backbone network of the model training module adopts a feature pyramid sharing convolution module to reinforce the multi-scale detail extraction capability; the neck network introduces an advanced screening path aggregation network and a selective feature fusion module to realize dynamic feature screening and fusion; the detection head is integrated with an MCFEM module, and shielding perception and scale adaptability are enhanced. According to the method, the problems of high omission ratio and poor robustness caused by large defect scale change, serious shielding and complex background in drainage pipeline detection are effectively solved, the small target defect identification precision and the shielding scene detection accuracy are remarkably improved, and the method is suitable for high-precision and light-weight detection of multi-scale defects in a complex shielding environment.

The invention discloses a self-service door opening method for a store, and relates to the technical field of self-service stores. The system carries out intelligent matching according to a pre-stored user file, calculates a similarity threshold value through an algorithm, judges that a user is a legal user if the matching degree exceeds a preset value, or rejects access; a dynamic combination strategy is adopted to allow an administrator to configure weights and combination modes of different fields according to the security requirements of the store, so that the user experience is optimized and the privacy leakage risk is reduced on the premise of ensuring the security; a background management system flexibly sets a weight value and combinatorial logic of each verification element, the matching efficiency is dynamically optimized based on a preset similarity threshold, if a comprehensive score after element combination reaches a security level score configured by the system, rapid door opening is automatically authorized, otherwise, secondary verification or manual auditing is triggered, and the safety of the system is ensured. The false rejection rate is reduced, the safety protection capability is improved, the verification modes are automatically switched according to regions or time periods, and the door opening speed is high when the operation is successful.

The invention provides a workpiece double-sided defect identification method and equipment based on multi-view visual inspection, and relates to the technical field of industrial machine vision, after a workpiece is migrated to a transparent detection table, a light source is driven to be dynamically switched according to a light source time sequence, and a multi-angle image sequence is synchronously captured; and segmenting an image sequence by taking a double-sided area of the workpiece as a constraint, generating an array type multi-angle segmentation sub-image of a light source parameter index, and then outputting a double-sided defect panoramic distribution thermodynamic diagram through defect identification. The technical problems that in the prior art, due to the fact that workpiece overturning detection efficiency is low, synchronous imaging of double-face defects is difficult, and the defects are obviously interfered by ambient light, the defects lack space quantification basis, the false detection rate is high, and sorting decision is interfered are solved. The technical effects of sub-millimeter spatial positioning precision, multi-dimensional risk quantitative mapping and full-process automatic sorting decision closed loop of double-sided defects of the workpiece are achieved, and the reliability and processing efficiency of industrial quality inspection are remarkably improved.

The application discloses to the electric power technical field, specifically for a kind of electric power worker goggles wearing detection method based on instance segmentation, including specific steps as follows: the data set D1 of original electric power worker wearing goggles operation image is constructed;D1 is preprocessed, and the data set D2 of new electric power worker wearing goggles operation image is obtained;An EGSNet network is designed, and the network is used to process any electric power worker operation image in D2, and the wearing detection result of electric power worker goggles is obtained.The application generates noise filter related to each goggles instance dynamically through noise disturbance and reverse noise reduction mechanism, effectively captures the boundary features of goggles, realizes more accurate boundary processing;Mask feature map provides global context information, further enhances the robustness of segmentation in complex background, significantly reduces the false rejection rate and false detection rate, especially when the goggles and background texture or color are similar.

This invention discloses a method and system for suppressing false rejection behavior and selectively forgetting harmful semantics in large language models across vertical domains based on feature subspace decoupling, belonging to the field of fine-tuning and alignment technology for large artificial intelligence models. The method includes steps for target definition and data construction, feature subspace localization, key level optimization, orthogonal decoupling weight correction, constrained norm renormalization, selective fine-tuning, false rejection calibration, and closed-loop verification monitoring and document output. The system includes modules for concept discovery and data construction, representation subspace modeling, false rejection localization and calibration, and verifiable evaluation and continuous monitoring. This invention can significantly reduce the false rejection rate and maintain a safety baseline while preserving the model's generalizability, meeting the compliance requirements of generative artificial intelligence services.

The invention discloses an anti-electric-shock capacitive-resistive screen fused with pressure induction, and relates to the technical field of touch screens, the capacitive-resistive screen comprises a capacitive touch layer and a resistive pressure induction layer, the capacitive touch layer is used for detecting coordinate information of a touch position, the resistive pressure induction layer is used for detecting a pressure signal applied to the screen, and the capacitive touch layer is used for detecting the coordinate information of the touch position. The touch screen further comprises a processing unit, and the processing unit is electrically connected with the capacitance touch layer and the resistance pressure sensing layer and used for executing the following operation. According to the pressure-sensing-fused mistaken-electric-shock-preventing capacitive-resistive screen, accurate analysis of a touch intention is achieved by constructing a dynamic pressure fingerprint discrimination and self-adaptive threshold model. According to the scheme, a multi-level signal processing and decision-making mechanism is adopted, the dynamic click pressure and the static background pressure can be effectively distinguished, the problem that a traditional single pressure threshold criterion is high in misjudgment rate in a composite pressure scene is solved, and therefore the accuracy and reliability of touch operation are improved.

The present application belongs to the technical field of quality detection, and particularly relates to a kind of axle assembly quality detection method based on machine vision.Firstly, the static image of axle is collected, after adaptive filtering and edge sharpening processing, the improved YOLOv8 with series gap feature attention module is used to extract static parameters and compare; after passing, the fastener pretightening force is detected first, then the dynamic image and vibration data are collected by simulating working condition, after motion blur compensation of dynamic image and Kalman filter denoising of vibration data, the improved YOLOv8 extracts dynamic parameters and compares; multiple cycles of detection, and the axle assembly quality is determined to be qualified if all qualified.The present application covers all working conditions, improves detection accuracy and reliability, and reduces the false rejection rate.

Systems and methods for performing testing of a single analyte on a group of multiple clinical diagnostic analyzers, or a single clinical diagnostic analyzer having multiple analytic units, or combinations thereof, are disclosed. A mean and SD for each individual instrument are input to at least one of the instruments along with a QC rule to be used, the probability of false rejection function for the QC rule, and a desired false rejection rate. A group mean and a group SD are calculated to satisfy the desired false rejection rate and QC rule and loaded into each individual instrument for use in testing the single analyte at each individual instrument.

The invention relates to the technical field of information security, in particular to a cloud edge collaborative access module test method and system based on biological behavior recognition, and the method comprises the steps: a structure edge end collects user biological behavior data and carries out the primary processing, and obtains biological behavior feature data; synchronizing the biological behavior characteristic data to the cloud; the cloud performs feature analysis and authentication decision on the received biological behavior feature data; generating a test scene containing a legal access request and an illegal access request in the cloud edge collaborative environment; calculating an error acceptance rate and an error rejection rate of the access module based on the test result; according to the method, the security test of the access module is performed by simulating an attack scene, so that edge collection and cloud analysis cooperative processing of the biological behavior data are realized, and the access accuracy and security of the access module can be effectively evaluated; and by introducing an error acceptance rate, an error rejection rate and a plurality of attack simulation tests, the method has relatively high accuracy and applicability in performance evaluation and security verification.

The intelligent apple slice fine sorting and drying equipment comprises a conveying mechanism, a height limiting mechanism is mounted at the feeding end of the conveying mechanism, the conveying mechanism comprises a mounting side plate, and a conveying belt is mounted on the inner side of the mounting side plate; a plurality of protruding strip-shaped structures are arranged on the outer surface of the conveying belt at equal intervals. The intelligent selection area comprises a multispectral imaging mechanism, a color grading mechanism and a shape screening mechanism. Multi-spectral fusion detection: RGB + NIR + HDR imaging is combined to improve a YOLOv7 model, the defect detection rate is improved, the error rejection rate is reduced, dynamic color grading, HSV and spectral feature splicing + FCM clustering are adopted, incremental learning is supported, variety differences are adapted, the color sorting accuracy is improved, and the color sorting efficiency is improved. And meanwhile, 3D shape screening, laser triangulation and Poisson curved surface reconstruction are adopted, so that the warping degree detection precision is improved, and the rejection rate of deformed pieces is increased.

The invention relates to the technical field of radar body detectors, and particularly discloses a gesture mode switching method and system for a radar body detector, and the method comprises the steps: obtaining a radar echo signal, and extracting the motion parameter information of a user according to the radar echo signal; generating a motion state index sequence according to the motion parameter information; analyzing the motion state index sequence, detecting a signal segment whose similarity with a radar characteristic mode of a preset gesture is greater than a first preset threshold, and marking the signal segment as a potential gesture signal; based on context intention judgment, analyzing the potential gesture signal to obtain an intention judgment score, and judging whether the potential gesture signal is a mode switching instruction; according to the method, the conscious mode switching instruction and the unconscious background motion of the user are effectively distinguished, gesture variation caused by the position and posture change of the user is adapted, and the effects of remarkably reducing the misjudgment rate and improving the gesture interaction accuracy and reliability are achieved.

The application relates to the technical field of radar body detectors, and particularly discloses a radar body detector gesture mode switching method and system, wherein the method comprises the following steps: acquiring a radar echo signal, and extracting motion parameter information of a user according to the radar echo signal; generating a motion state index sequence according to the motion parameter information; analyzing the motion state index sequence, detecting a signal segment with a radar feature mode similar to a preset gesture and greater than a first preset threshold, and marking the signal segment as a potential gesture signal; and based on context intention judgment, analyzing the potential gesture signal to obtain an intention judgment score, and judging whether the potential gesture signal is a mode switching instruction; the method effectively distinguishes between a conscious mode switching instruction of a user and an unconscious background motion, and is adapted to gesture variation caused by changes in the position and posture of the user, so that the false rejection rate is significantly reduced, and the gesture interaction accuracy and reliability are improved.

The invention relates to a quick identity authentication method and device based on physical unclonable features, equipment and a medium, and the method comprises the steps: taking a query feature descriptor as a retrieval object, and carrying out approximate nearest neighbor matching retrieval in a local feature descriptor set of a global feature library, after screening, determining one or more candidate physical unclonable tag identities through voting; for candidate physical unclonable tag identities, corresponding registered key point space coordinates are called from a geometric feature library, and a re-projection error threshold is combined through a random sampling consistency algorithm; checking whether the space coordinate of the query key point and the space coordinate of the registered key point of the candidate physical unclonable tag meet a preset geometric transformation model or not, and calculating a geometric consistency score according to the preset geometric transformation model; and if it is detected that the geometric consistency score is greater than or equal to a preset score threshold, outputting an identity authentication success result. According to the invention, the identity authentication efficiency is greatly improved, and the false rejection rate of identity authentication is remarkably reduced.

This invention discloses a dynamic role-based access control method based on dual-source trust fusion to address the high risk of unauthorized access caused by static role authorization in dynamic network environments. The method first receives user access requests and extracts contextual risk features. Then, it extracts historical user interaction indicators and calculates dynamic behavior trust scores based on time decay. External feedback scores are obtained, outlier scores are removed, and weighted aggregation yields robust feedback trust scores. Then, based on data consistency and divergence, adaptive weighting is applied to derive a comprehensive trust score. Finally, the comprehensive trust score is coupled with the contextual risk value to determine the trust gap, and based on this, full authorization, partial authorization downgrade based on sensitivity truncation, or access denial are performed. This invention abandons static fixed weights, enhancing the robustness of trust assessment in extreme scenarios; and it pioneers a partial authorization pruning mechanism, effectively reducing the false rejection rate of legitimate users while ensuring security, achieving a balance between system availability and the principle of least privilege.

The invention discloses a wafer surface colloid feature acquisition device, and belongs to the field of wafer detection. According to the invention, the technical problems of low accuracy and high missing detection rate and false detection rate when the existing traditional image acquisition device is used for acquiring the characteristics of the colloid on the surface of the wafer are solved. The support is fixedly installed on the optical platform, the placing tray is fixed at the center of the upper surface of the optical platform, and the wafer is placed at the center of the upper surface of the placing tray; the display screen module is installed on the upper right portion of the support, the bright field camera module is installed on the upper left portion of the support, the display screen module and the bright field camera module are arranged in an axial symmetry mode, the area light source module is installed on the upper portion of the support, and the dark field camera module is installed on the upper portion of the front side of the support. Light emitted by the area light source module reaches the surface colloid of the wafer and forms diffuse reflection light, and the dark field camera module is used for receiving the diffuse reflection light formed by the surface colloid of the wafer. The detection accuracy is improved, and the missing detection rate and the false detection rate are reduced. The method is used for collecting the characteristics of the colloid on the surface of the wafer.

The application discloses a finger vein recognition method and system based on dynamic balance of false recognition rate and false rejection rate, and the method comprises the following steps: obtaining a to-be-recognized finger vein image, and performing image preprocessing and ROI extraction processing to obtain an ROI region of the finger vein image; a finger vein recognition model is constructed, three-stage hybrid training is performed in combination with the ROI region of the finger vein image, and a trained finger vein recognition model is obtained; a balanced error rate evaluation index is constructed to evaluate the trained finger vein recognition model, and an evaluated finger vein recognition model is obtained; and finger vein recognition is performed on the to-be-recognized finger vein image based on the evaluated finger vein recognition model, and a finger vein recognition result is obtained. The application can meet the finger vein recognition requirements in multiple scenes and improve the finger vein recognition accuracy. The application can be widely applied to the technical field of finger vein recognition as a finger vein recognition method and system based on dynamic balance of false recognition rate and false rejection rate.

The invention discloses a payment data management method and system based on an AI robot, and relates to the technical field of payment data management, and the method comprises the steps: collecting multi-dimensional data, carrying out the preprocessing, and generating credible and uncredible evidence probability values; based on credible and uncredible evidence probability values, constructing a quality function and an identification framework of multi-dimensional data, calculating a similarity value according to the identification framework, calculating a conflict measure and a support degree between evidences in combination with the quality function, and generating a boundary threshold value of a reward-punishment mechanism; calculating the final weight of the quality function by using a Deng entropy and a reward-penalty mechanism, weighting the quality function, executing two-stage linear weighted fusion, judging a fusion result by using a maximum credibility criterion, and generating a judgment result; according to the invention, the false identification rate and the false rejection rate are obviously reduced, so that the payment data management process is more intelligent and reliable.

The application discloses an instruction tamper-proofing device for a traffic information board system, relates to the field of traffic information security, and solves the three technical problems of key clonable risk, high algorithm dependence and poor environmental adaptability existing in traditional encryption schemes. A tamper-proofing system is constructed through a triple synergy mechanism: unique unclonable physical characteristics are extracted based on a physically unclonable circuit, efficient integrity verification is realized through a segmented cascading parity check circuit, and time stamps are accurately compared in combination with a temperature compensation clock; and multi-dimensional features are fused and integrated, tamper identification is performed through feature comparison, irreversible hardware failure is formed to trigger tamper identification, and ultimate protection is formed. The device achieves a pure hardware millisecond-level response, completely eliminates software dependence, maintains a zero false rejection rate in extreme environments, ensures the safety of the whole life cycle of the instruction through physical-level protection, and provides uncopyable security protection for the information board system.

The invention discloses a children voiceprint self-adaptive correction method and a children voiceprint self-adaptive correction system. The method comprises the steps of obtaining a target child voice signal; multi-dimensional voiceprint features are extracted from the target child voice signal, normalization processing is carried out, a high-dimensional voiceprint feature vector is constructed, and the multi-dimensional voiceprint features comprise MFCC, fundamental frequency and formant; the Euclidean distance between the high-dimensional voiceprint feature vector and the reference high-dimensional voiceprint feature vector is calculated, and a judgment threshold value is combined to carry out matching judgment, so that the final child voiceprint is determined; wherein the judgment threshold is dynamically adjusted by using historical matching data to adapt to sound changes, and the reference high-dimensional voiceprint feature vector is a voiceprint template obtained by combining a screened sample with confidence meeting requirements with a moving average method to progressively update. By implementing the method provided by the invention, the template and the threshold can be dynamically adjusted in combination with a self-adaptive correction mechanism, the error rejection rate is reduced on the premise of ensuring the safety, and the robustness and accuracy of the system when facing the child sounding behavior mode change are improved.

The application provides a security event early warning and response method based on an operator-level network, comprising: collecting login failure frequencies and verification timeout times of each authentication node of the operator-level network, obtaining time characteristics of abnormal authentication requests according to time interval statistical distribution of user password error retries, judging whether a certificate expiration trigger threshold is within a preset range to obtain preliminary authentication anomaly distribution data; according to an identification result of the potential threat, dynamically adjusting authentication security policy parameters of the certificate expiration trigger threshold and a token refresh failure ratio, reducing a biometric identification false rejection rate through session hijacking detection delay time optimization, and obtaining system overall security protection effect evaluation data after optimization of an authority verification response time.

The utility model discloses an ampoule bottle breaking and falling detection device, relates to the technical field of medicine packaging equipment, and aims to solve the problems that a visual system is high in cost and easy to be interfered by ambient light, a photoelectric sensor is sensitive to transparency of a bottle body, the false detection rate is high, the manual detection efficiency is low, and the detection cost is high in the conventional detection mode. According to the key points of the technical scheme, the device comprises a supporting base, a holding seat is fixedly installed in the middle of the upper surface of the supporting base, a material moving groove is formed in the middle of the holding seat, an adjustable support is fixedly installed on the upper surface of the supporting base, and the adjustable support is fixedly installed on the upper surface of the supporting base. A microswitch is fixedly installed on the installation position of the adjustable support, a touch control strip is arranged on the microswitch, and one end of the touch control strip is arranged above the material moving groove of the holding base and attached to the side surface of the ampoule bottle moving in the material moving groove. The effects of reducing the false detection rate, reducing the cost and improving the detection efficiency are achieved.

The application provides a weld quality detection method and a training method. The weld quality detection method comprises the following steps: obtaining a first gray-scale image, wherein the first gray-scale image is obtained by sequentially irradiating a detected object by at least two light sources, the number of the first gray-scale image corresponds to the number of the light sources, and the light sources output parallel light. A first normal angle image of the detected object is obtained based on the first gray-scale image. The first normal angle image is divided into a marked area. And the first normal angle image and the division result of the marked area are output and / or displayed to obtain a weld quality detection result. More information is obtained based on the first normal angle image, and the information itself is more accurate, which can improve the detection accuracy of the weld quality detection, thereby solving the problem of high false rejection rate and high false acceptance rate in the prior art when the weld quality of a measured object with high surface reflectivity is detected.