Patents
Literature
Patsnap Copilot is an intelligent assistant for R&D personnel, combined with Patent DNA, to facilitate innovative research.
Patsnap Copilot

42 results about "Matrix embedding" patented technology

Stony desertification region vegetation ecological system and reestablishing method thereof

InactiveCN106888791AGuarantee the sustainable growth in the later stageNo need for manual watering drippersPlant cultivationCultivating equipmentsWater storagePlanting seed
The invention discloses a stony desertification region vegetation ecological system and a reestablishing method thereof. The vegetation ecological system is high in water storage capacity, plants grow easily, and the vegetation ecological system in the stony desertification region can be reestablished fast. The vegetation ecological system comprises a ground, multiple arbor planting matrixes and multiple shrub growing matrixes are arranged on the ground, a herbal growth carrier is laid in the other regions of the ground, arbors are planted in the arbor planting matrixes, shrubs are planted in the shrub growing matrixes, and herbal plants are planted in the herbal growth carrier. The reestablishing method includes the following steps that the arbor planting matrixes are prefabricated; planting matrix embedding holes are dug, holes for inserting water absorbing roots are drilled, the water absorbing roots are inserted into the holes, the arbor planting matrixes are placed, and arbor saplings are planted; the shrub growing matrixes are formed through a blast method, and the herbal growth carrier is laid; after deadwood fallen leaves, dinas soil mass generated by overland runoff are converged in the shrub growing matrixes and attached to the surface of the herbal growth carrier, and then shrub and herbal plant seeds are manually broadcast.
Owner:CHONGQING JIAOTONG UNIVERSITY

Method for processing software watermark information on the basis of thread relationship

The invention relates to a method for processing software watermark information on the basis of a thread relationship. The method comprises an embedding process and an extracting process of a software watermark; the embedding process comprises the following steps: pre-processing the software watermark and a host program, generating a software watermark matrix; monitoring an execution process of the host program, and generating a thread relationship matrix; scrambling the thread relationship matrix to obtain a disorder thread relationship matrix; embedding the software watermark matrix into the disorder thread relationship matrix, carrying out inverse scrambling processing and restoring to an order thread relationship matrix; modifying a source code of the host program according to the order thread relationship matrix to obtain the final program embedded with the software watermark, wherein the extracting process is opposite to the extracting process, and the software watermark matrix is extracted after being scrambled via the thread relationship matrix embedded with the software watermark, and then the software watermark is extracted from the software watermark matrix. Compared with the prior art, the software watermark is embedded by the existing relationship between the threads in the program, and the software watermark is extracted by detecting the thread relationship in the program with the software watermark, so that the method has the advantages of high data rate, imperceptibility and resistivity.
Owner:TONGJI UNIV +1

Remote sensing image multi-label classification method based on adjacent matrix guide label embedding

The invention provides a remote sensing image multi-label classification method based on adjacency matrix guide label embedding. The method comprises the following steps: obtaining a training sample set, a test sample set, an adjacency matrix and a label vector matrix; constructing a remote sensing image multi-label classification model based on adjacent matrix guidance label embedding; iteratively training the remote sensing image multi-label classification model based on adjacent matrix guidance label embedding; and obtaining a multi-label image classification result. The label vector matrix embedding process is constrained through the minimum mean square error loss of the adjacent matrix and the embedded vector cosine similarity matrix, the prior information of the adjacent matrix is fully considered, and the mF1 value of multi-label image classification is improved; by introducing a label and image collaborative embedding method, joint modeling is performed on a response relationship between a label and each pixel in a feature map, so that the influence of a remote sensing image background on multi-label image classification is reduced, and the mF1 value of multi-label image classification is further improved.
Owner:XIDIAN UNIV

Retrospective off-respirator respiration gating method of cardiac image sequence

The invention provides a retrospective off-respirator respiration gating method of a cardiac image sequence. According to the method, firstly the Laplacian eigenmap in a manifold learning method is used to carry out dimensionality reduction processing on a matrix with the storage of ECG gating cardiac image sequence data to obtain a low-dimensional coordinate matrix embed in a high-dimensional observation data point set, then the Euclidean distance between adjacent feature vectors in the low-dimensional coordinate matrix is calculated, the local maxima of the Euclidean distance is detected and is used as the selection position of a gated frame, and thus a gating image sequence with the removal of respiration motion artifact is obtained. According to the method, the matrix formed by the gray values of all pixels in an image is directly analyzed, and the respiration motion information in the cardiac image sequence is obtained. According to the method, only the solution of the feature value of a sparse matrix is needed, the manual involvement of an operator is not needed, and the method has the advantages of low computational complexity, high degree of automation, and low application cost. Furthermore, only local distance information is used in the method, and a gating result is not sensitive to noise.
Owner:NORTH CHINA ELECTRIC POWER UNIV (BAODING)

A Retrospective Offline Respiratory Gating Method for Cardiac Image Sequences

The invention provides a retrospective off-respirator respiration gating method of a cardiac image sequence. According to the method, firstly the Laplacian eigenmap in a manifold learning method is used to carry out dimensionality reduction processing on a matrix with the storage of ECG gating cardiac image sequence data to obtain a low-dimensional coordinate matrix embed in a high-dimensional observation data point set, then the Euclidean distance between adjacent feature vectors in the low-dimensional coordinate matrix is calculated, the local maxima of the Euclidean distance is detected and is used as the selection position of a gated frame, and thus a gating image sequence with the removal of respiration motion artifact is obtained. According to the method, the matrix formed by the gray values of all pixels in an image is directly analyzed, and the respiration motion information in the cardiac image sequence is obtained. According to the method, only the solution of the feature value of a sparse matrix is needed, the manual involvement of an operator is not needed, and the method has the advantages of low computational complexity, high degree of automation, and low application cost. Furthermore, only local distance information is used in the method, and a gating result is not sensitive to noise.
Owner:NORTH CHINA ELECTRIC POWER UNIV (BAODING)

Method for production of metal foam or metal-composite bodies

A method for the production of foamable or foamed metal pellets, parts and panels. The method comprises the steps of: i) providing a mixture of a metal alloy powder with a foaming agent powder, ii) pre-compacting the mixture of step i); iii) heating the pre-compacted mixture of step ii) to a temperature below a decomposition temperature of the foaming and at which permanent bonding of the particles occurs v) hot compacting the body for producing a compacted body made of a metal matrix embedding the foaming agent; and vi) reducing the compacted body into metal fragments and thereby obtaining dense foamable metal chips. A method for the production of a foam metal using a closed volume metal shell is also disclosed. The method comprises the steps of: a) providing metal pieces and reducing said metal pieces into smaller metal particles; b) mixing the metal particles with an additive having a decomposition temperature that is greater than a solidus temperature of said metal particles; c) pouring the mixture of step b) into a closed volume metal shell having a given thickness and providing the metal shell with at least one passage for gases to escape; d) reducing the thickness of the metal shell by applying pressure; e) heating the metal shell to a temperature above said solidus temperature of the metal particles and below said decomposition temperature of the additive, and immediately applying pressure on the metal shell sufficient to compress the metal particles and to create micro shear conditions between the metal particles so as to obtain a dense metal product.
Owner:AGS TARON INVESTMENTS INC

Graph embedding method based on adaptive graph learning

The invention discloses a graph embedding method based on adaptive graph learning. The graph embedding method comprises four steps of constructing a graph auto-encoder framework, performing Laplace embedding, performing adaptive learning on an adjacent matrix and performing iterative updating solution. A two-layer graph convolutional neural network is adopted in the coding layer part of the graph auto-encoder frame, and the reconstruction loss of an adjacent matrix is formed in the decoding layer part; the Laplace embedding part is used for embedding a Laplacian matrix into a potential space, so that a sample point can be more accurately mapped to a projection subspace; the adaptive learning of the adjacent matrix is divided into three steps: 1, the fixed number of node neighbors is not adopted any more, but normal distribution is obeyed, so that variables which can be obtained through the adaptive learning are formed; 2, a threshold value for stopping iteration is set, and updating is stopped when the number of iterations is greater than the threshold value; 3, part updating of the adjacent matrix is expressed by the formula in the specification; and finally,a model solving method is provided in an iterative updating solving part. The method is high in robustness and wide in application range, and the application range of the graph auto-encoder is greatly expanded.
Owner:NORTHWESTERN POLYTECHNICAL UNIV

Method for processing software watermark information on the basis of thread relationship

The invention relates to a method for processing software watermark information on the basis of a thread relationship. The method comprises an embedding process and an extracting process of a software watermark; the embedding process comprises the following steps: pre-processing the software watermark and a host program, generating a software watermark matrix; monitoring an execution process of the host program, and generating a thread relationship matrix; scrambling the thread relationship matrix to obtain a disorder thread relationship matrix; embedding the software watermark matrix into the disorder thread relationship matrix, carrying out inverse scrambling processing and restoring to an order thread relationship matrix; modifying a source code of the host program according to the order thread relationship matrix to obtain the final program embedded with the software watermark, wherein the extracting process is opposite to the extracting process, and the software watermark matrix is extracted after being scrambled via the thread relationship matrix embedded with the software watermark, and then the software watermark is extracted from the software watermark matrix. Compared with the prior art, the software watermark is embedded by the existing relationship between the threads in the program, and the software watermark is extracted by detecting the thread relationship in the program with the software watermark, so that the method has the advantages of high data rate, imperceptibility and resistivity.
Owner:TONGJI UNIV +1
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products