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65 results about "Scale weight" patented technology

A weight scale is any device used to determine the weight of an object; it normally includes a scale that indicates the weight or compares the object to calibrated known weights.

Deep learning model based on multi-scale network and application in brain state monitoring

A deep learning model based on a multi-scale network and application in brain state monitoring are provided. A model establishing method comprises steps of: preprocessing and multi-scale transforming a measured multichannel signal; obtaining a multi-scale weighted recursive network and a cross-recursive rate matrix corresponding to the multi-scale weighted recursive network of the multichannel signal in all scales; extracting the network indexes of the multi-scale weighted recursive network at different scales; at each scale, retaining relatively large elements in the cross recursive rate matrix and obtaining an unweighted adjacent matrix and a multi-scale unweighted recursive network corresponding thereto; for each value of a variable in the set range, obtaining the multi-scale unweighted recursive network and the adjacent matrix corresponding to the multi-scale unweighted recursive network, extracting the network indexes of the multi-scale unweighted recursive network at different scales, calculating the integral of the network indexes when the variable is changed in the set range, and the integral as the final network index of the multi-scale unweighted recursive network under each scale; and training the deep learning model and monitoring a brain state.
Owner:钧晟(天津)科技发展有限公司

Binocular visual multi-line projection structured light calibration method

The invention discloses a binocular visual multi-line projection structured light calibration method. The method comprises the following steps that 1) the sequence numbers of light stripes are determined; 2) left and right cameras collect a lattice image, four corners of a lattice are clicked, initial estimated positions of other intersection points in the lattice are obtained, and sub-pixel coordinates of intersection points are obtained by using an Ostu threshold method and a gray scale weighted average method in a k*k neighborhood of the initial estimated positions of intersection points; 3) 3D coordinates of the intersection points are obtained; and 4) the steps 1-3 are repeated, the 3D coordinates of the intersection points obtained in multiple times are classified according to the sequence numbers of the light stripes, for all points belonging to the same structured light plane, a least square method is used to carry out planar fitting on the 3D coordinates of the intersection points belongs to the same structured light to obtain a plane equation, and calibration is not completed until all the structured light planes are in the planar equation of the system coordinate system. The method has the advantages that a calibration board has no requirements for planarization, manufacture is simple, calibration is flexible, no auxiliary equipment is needed, the method is suitable for onsite calibration and the versatility is high.
Owner:SOUTH CHINA UNIV OF TECH

Uterine neck cell image characteristic identification method and uterine neck cell characteristic identification apparatus

The invention provides a uterine neck cell image characteristic identification method and a uterine neck cell characteristic identification apparatus. The uterine neck cell image characteristic identification method comprises the following steps: S100, converting a uterine neck cell color picture into a gray-scale image; S200, segmenting the uterine neck cell grey-scale image by use of a mean value segmentation method to extract nuclei of uterine neck cells; S300, accurately positioning the centers of the nuclei by use of a gray scale weight center positioning method; S400, converting a uterine neck cell image in a cartesian coordinate system into a uterine neck cell image in a polar coordinate system; S500, taking a vector composed of a gray-scale median value of the uterine neck cell image on each polar radius in the polar coordinate system as a characteristic vector of the uterine neck cell image; and S600, training a support vector machine vector machine classifier by use of a uterine neck cell training sample and performing class determination on the image of the uterine neck cell training sample by use of the classifier. Compared to geometrical characteristics extracted by use of a conventional method, the uterine neck cell image characteristic identification method has the advantages of dimension invariability, rotation invariability, high identification rate and fast identification speed.
Owner:GUANGXI NORMAL UNIV

Disjoint-view object matching method based on corrected weighted bipartite graph

The invention provides a disjoint-view object matching method based on a corrected weighted bipartite graph. The method relates to the field of computer vision. The method expresses a disjoint-view object matching problem as a maximum posterior probability problem, so that an object observation model and time-space constraints of a surveillance network are combined, and the maximum posterior probability problem is resolved through solving the maximum weight matching of a weighted bipartite graph. To solve the problem that construction of a common weighted bipartite graph is liable to introduction of incorrect matching, the method provides a corrected weighted bipartite graph construction method based on an adaptive threshold, so that incorrect matching is prevented from being introduced during construction of the weighted bipartite graph as much as possible. Aimed at the defect of a conventional KM method that the amount of computation is too large during large-scale weighted bipartite graph matching problem solving, the method brings forward a MH sampling-based method for approximating and solving the maximum weight matching of the weighted bipartite graph, so that a disjoint-view object matching relationship is obtained.
Owner:SOUTHEAST UNIV

Multi-scale segmentation-based saliency detection method

The invention relates to a multi-scale segmentation-based saliency detection method. The method includes the following steps that: 1: smoothing image processing is performed on an input image through using bilateral filtering parameters, super-pixel segmentation of different segmentation scales is performed on the processed input image, global smoothness is calculated according to super-pixels obtained through segmentation, the global smoothness and the bilateral filtering parameters are combined to build an adaptive algorithm function adopting a segmentation effect as an objective, bilateral filtering parameters under different scales are solved, and super-pixel points in the optimal smoothed image are obtained; sep 2, initial foreground seeds are obtained through using a target likelihood graph technique, the boundary of the image is adopted as initial background seeds, background seeds and foreground seeds are selected from the initial background seeds and the initial foreground seeds by using a cross-validation method, and a background-based RBB saliency map and a foreground-based RFB saliency map are generated; and step 3, the scale weights of the super-pixels and the seed weights of the background seeds and the foreground seeds are calculated, and the obtained RBB saliency map and RFB saliency map are combined, so that a final saliency map can be obtained.
Owner:HUZHOU TEACHERS COLLEGE

Belt scale weight calibration method equivalent to material calibration

The invention relates to a belt scale weight calibration method equivalent to material calibration, comprising the following steps: S1, testing the integrating factors Ks and Km of a belt scale under material calibration and weight calibration modes respectively; S2, calculating the proportionality coefficient K (K=Ks/Km) of the integrating factors Ks and Km according to Ks and Km; S3, calculating the current material calibration integrating coefficient Kxs (Kxs=K*Kxm) corresponding to the current weight calibration integrating coefficient Kxm according to the integrating coefficient Kxm of the belt scale under the current weight calibration mode and the proportionality coefficient K; and S4, using the current material calibration integrating coefficient Kxs to replace the current weight calibration integrating coefficient Kxm. The determined relationship of the same calibration precision parameter under different calibration modes is found out through research on the equivalence of a belt scale under the same internal and external conditions and different calibration modes and precision, and a calibration mode with low requirement on calibration conditions is used to replace a calibration mode with high requirement on calibration conditions. Convenient, timely, accurate and low-cost calibration is realized.
Owner:SD STEEL RIZHAO CO LTD
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