6results about How to "Improve match quality" patented technology

The invention relates to the technical field of task allocation, in particular to a task allocation method for flexible employment. According to the technical scheme, the method comprises the following steps that a database of related information of tasks and employees is constructed, wherein the database comprises detailed information of the tasks and comprehensive information of the employees; respectively constructing a task model and an employee portrait based on the information in the database; and matching the task with the employee through an intelligent matching algorithm, wherein the intelligent matching algorithm comprises matching algorithm selection and optimization, real-time matching and dynamic adjustment, and multi-objective optimization and tradeoff. According to the method, multiple matching algorithms are combined for optimization, weights are selected and adjusted according to tasks and employee characteristics, accurate matching is achieved, a task model and employee portrait multi-dimension consideration adaptability is achieved, adaptive changes are matched in real time, tasks and multiple aspects of employees are optimized and balanced in a multi-objective mode, the development of rights and interests of the employees is considered, and the matching quality, the working enthusiasm and the stability are improved; flexible employment resources are managed more effectively, and the task allocation effect is improved.

The invention discloses a multi-region transportation service mode matching method and system, and particularly relates to the technical field of transportation services, and the method comprises the following steps: dividing user identities into order-sending users and order-receiving users, and respectively obtaining an order-sending requirement set of a target order-sending user and a service set of all order-receiving users in a non-order-receiving state; hard condition screening is firstly carried out, order receiving users meeting hard conditions are reserved, and then elastic condition screening is carried out; if the order receiving users meeting all the elastic conditions exist, direct matching is carried out; otherwise, carrying out portrait analysis by using K-means clustering based on the historical record of the target order issuing user, and evaluating a matching failure rate; according to a failure rate result, negotiation communication channels are successively established until consistent matching is achieved; the method can deeply understand the demand characteristics and behavior patterns of the order issuing user, provides highly personalized matching services, improves the service quality of the platform, and further enhances the loyalty and satisfaction of the user.

The application discloses a wave image matching method based on fusion matching cost, and relates to the field of stereo matching, and comprises the following steps: S1, left and right eye images of waves are collected by using binocular cameras to determine a disparity range; S2, the left and right eye images of original waves collected in the step S1 are preprocessed; S3, a matching cost value of the wave images is obtained by using an improved Census algorithm; S4, improved Census cost, AD cost and gradient cost are fused to obtain a cost space; S5, a cross-domain is used for cost aggregation; S6, a winner-takes-all (WTA) strategy is used to calculate the disparity of the wave images; S7, the disparity map in the step S6 is subjected to left-right consistency checking, and is subjected to hole filling and sub-pixel optimization processing. The application adopts the above method, solves the problem that the disparity map obtained from the wave images is prone to a large number of invalid points and mismatching points, improves the correctness of wave stereo matching, and guarantees the matching precision of the depth discontinuous region.

The invention relates to a quartz flexible accelerometer, and aims to solve the problems that when an existing torquer pairing method is used for matching a torquer with a large data size, time and labor are wasted, the pairing effect cannot be optimal, and the success rate is low. The quartz flexible accelerometer torquer pairing method based on the Hungary algorithm comprises the following steps: numbering M upper torquers and N lower torquers, and respectively testing height difference values between magnetic pole piece surfaces and yoke C surfaces of each upper torquer and each lower torquer, sorting and recording all test data according to the test data and magnetic saturation values of corresponding points on each upper torquer and each lower torquer; calculating and screening an upper torquer and a lower torquer which meet matching conditions, and creating a bipartite graph of the upper torquer and the lower torquer; calculating the maximum matching logarithm and the optimal pairing number of the upper torquer and the lower torquer according to a Hungary algorithm; and sorting and archiving the matching result, thereby completing the pairing of the quartz flexible accelerometer torquer.

The present invention provides a method for eliminating false matches based on improved vector field consistency. The method achieves the purpose of improving the accuracy of feature matching and the stability of the reconstruction algorithm by eliminating feature points that are incorrectly matched during the image stereo reconstruction process, and provides more accurate parameter information for subsequent stereo reconstruction tasks. In addition, the elimination method combines the global semantic information extracted by the visual Transformer model with the feature descriptors that characterize local details to form a high-dimensional feature vector containing local and global information. Under the Bayesian framework, the improved VFC algorithm converts the interpolation problem into a solution process for maximum a posteriori probability estimation. A hidden variable is associated with each vector field sample to identify whether the sample is an inlier or an outlier, and matching expansion is performed through the Bayesian formula to retain the correct feature matching pairs as much as possible and find potential correct matching pairs.

The invention discloses a wave image matching method based on fusion matching cost, and relates to the field of stereo matching, and the method comprises the following steps: S1, collecting left and right eye images of waves through a binocular camera, and determining a parallax range; s2, preprocessing the left and right eye images of the original waves collected in the step S1; s3, obtaining a matching cost value of the wave image by using an improved Census algorithm; s4, fusing the improved Census cost, AD cost and gradient cost to obtain a cost space; s5, carrying out cost aggregation by adopting a cross domain; s6, calculating the parallax of the wave image by using a WTA strategy; and S7, performing left and right consistency check on the disparity map in the step S6, and performing hole filling and sub-pixel optimization processing. By the adoption of the method, the problem that a disparity map obtained from a wave image is prone to having a large number of invalid points and mismatching points is solved, the accuracy of wave stereo matching is improved, and the matching precision of a depth discontinuous area is guaranteed.