Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Identifiable geometry preserving adaptive graph embedding method and device, equipment and medium

An adaptive, graph embedding technology, applied in the field of pattern recognition, which can solve the problems of inability to adapt to different data samples, unreliability, and inappropriate structural information for data.

Active Publication Date: 2021-08-31
JIANGSU UNIV
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Based on the above technical problems, in order to solve the problem that the existing graph embedding method adopts partial composition which cannot adapt to different data samples, resulting in the problem that the structure information it reflects is not suitable for the data, unreliable or insufficient

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Identifiable geometry preserving adaptive graph embedding method and device, equipment and medium
  • Identifiable geometry preserving adaptive graph embedding method and device, equipment and medium
  • Identifiable geometry preserving adaptive graph embedding method and device, equipment and medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0028] In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present disclosure. Apparently, the described embodiments are some, not all, embodiments of the present disclosure. Based on the described embodiments of the present disclosure, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present disclosure.

[0029] The purpose of this application is to provide a method, device, equipment and medium for identifying geometry-preserving adaptive graph embedding, see figure 1 , the method includes: obtaining a high-dimensional data set, the high-dimensional data set includes a training set and a test set; constructing a discriminable geometr...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to the technical field of pattern recognition, and discloses an identifiable geometry preserving adaptive graph embedding method, a device, equipment and a medium, the method comprises the following steps: obtaining a high-dimensional data set, the high-dimensional data set comprising a training set and a test set, the training set further comprising corresponding category information; constructing an identifiable geometry preserving adaptive graph embedding model; inputting the training set into the identifiable geometry preserving adaptive graph embedding model, and solving to obtain a weight matrix and a projection matrix, wherein the weight matrix is used for optimizing the projection matrix; and projecting the test set through the projection matrix to obtain low-dimensional representation. The method solves the problem that the structure information reflected by an existing graph embedding method is unsuitable for data, unreliable or insufficient due to the fact that the existing graph embedding method cannot adapt to different data samples in a partial graph composition mode.

Description

technical field [0001] The present invention relates to the technical field of pattern recognition, and specifically refers to a method, device, equipment and medium for embedding an identifiable geometry-preserving adaptive graph. Background technique [0002] In recent years, pattern recognition has been applied to text, voice, fingerprint, remote sensing, medical diagnosis and other aspects. Massive data with high-dimensional features makes it difficult for researchers to directly mine the internal relationships and laws of the data. These data are large in quantity and high in dimension, which not only wastes a lot of storage space, but also brings unnecessary calculations, which brings many challenges to the research of related application fields. Therefore, extracting key features from the redundant features of high-dimensional data has become an important research topic in various fields such as pattern recognition, artificial intelligence, and computer vision. Feat...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06K9/62
CPCG06F18/22G06F18/214
Inventor 苟建平薛雅陈潇君柯佳欧卫华
Owner JIANGSU UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com