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

Image data target recognition enhancing method based on data map, information map and knowledge map

A technology of knowledge map and map, which is applied in the cross field of distributed computing and software engineering technology, can solve the problem of not being able to recognize unlabeled images, and achieve the effect of narrowing the recognition range

Active Publication Date: 2018-05-18
HAINAN UNIVERSITY
View PDF4 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Technical solution: The present invention is a strategic method, which can be applied to image target recognition of pictures or cameras, and helps to solve the problem that unidentified images cannot be recognized in current machine learning

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
  • Image data target recognition enhancing method based on data map, information map and knowledge map
  • Image data target recognition enhancing method based on data map, information map and knowledge map

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0017] The specific process of an image recognition method based on data graph, information graph, and knowledge graph architecture is as follows:

[0018] Step 1) corresponds to figure 2 In 001, according to the existing image resources, establish a framework based on data graphs, information graphs, and knowledge graphs;

[0019] Step 2) corresponds to figure 2 002 in , obtain the image to be recognized;

[0020] Step 3) corresponds to figure 2 In 003, the image to be recognized is divided into two modules of recognized image set {Bi} and unrecognized image A;

[0021] Step 4) corresponds to figure 2 In 004, data matching is performed between the unrecognized image A obtained in step 3 and the entity Ai of the data map, and the matching degree R is obtained by formula 1. Suppose that the entity attributes (including structure, color, feature, frequency, local structure, etc.) in the data map match the value of Ai , Represents one attribute that Ai can match with...

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 discloses an image data target recognition enhancing method based on a data map, an information map and a knowledge map, mainly aims to solve the problem that existing image recognitionmethods cannot recognize, train and centralize images with types unmarked and belongs to the technical cross field of distributed computing and software engineering. The method includes: starting froman existing image type recognition result based on an in-depth learning method, establishing a three-layer map according to known image resources; subjecting unrecognized image type to feature matching on the data map to obtain an initial matching result; subjecting recognized image type to relation matching on the information map to obtain an intermediate matching result; performing indirect interaction relation matching in the knowledge map, calculating credibility of the intermediate matching result, ranking, and recommending the matching image type with highest credibility to a user.

Description

technical field [0001] The present invention is an image data target recognition enhancement method based on a data map, an information map and a knowledge map. It is mainly used to solve the problem of image recognition that the existing image recognition methods cannot recognize the unlabeled categories in the training set, and belongs to the cross field of distributed computing and software engineering technology. Background technique [0002] Knowledge graphs have become a powerful tool for representing knowledge in the form of labeled directed graphs, which can endow textual information with semantics. A knowledge graph is a graph constructed by representing items, entities or users in the form of nodes, and linking nodes that interact with each other in the form of edges. The edges between nodes can represent any semantic relationship. The construction of knowledge graph is divided into three levels: information extraction, knowledge fusion and knowledge processing ac...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 段玉聪何诗情靖蓉琦宋正阳邵礼旭
Owner HAINAN UNIVERSITY
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