Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

A Visual Question Answering Problem Solving Method Based on Complex Network Analysis Method

A technology of complex networks and analysis methods, applied in the fields of computer vision and natural language processing, can solve problems such as insufficient attention model, and achieve the effect of effective mining

Active Publication Date: 2021-11-12
NANJING UNIV OF POSTS & TELECOMM
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, a large number of studies have shown that only focusing on the attention model does not seem to be enough

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
  • A Visual Question Answering Problem Solving Method Based on Complex Network Analysis Method
  • A Visual Question Answering Problem Solving Method Based on Complex Network Analysis Method
  • A Visual Question Answering Problem Solving Method Based on Complex Network Analysis Method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] Below in conjunction with accompanying drawing and specific embodiment, further illustrate the present invention, should be understood that these examples are only for illustrating the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various aspects of the present invention All modifications of the valence form fall within the scope defined by the appended claims of the present application.

[0034] A visual question answering method based on complex network analysis methods, including semantic concept network construction, non-random depth walk, image and text feature fusion, and classifiers. Semantic concept network construction aims to mine co-occurrence patterns of concepts to enhance semantics Expression, non-random deep walk realizes the mapping of complex network relations to low-dimensional features. On the basis of constructing image semantic conc...

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 a visual question-answering problem-solving method based on a complex network analysis method, including semantic concept network construction, non-random depth walk, image and text feature fusion, and a classifier. The semantic concept network construction aims to mine the co-occurrence of concepts Mode to enhance semantic expression, non-random deep walk realizes the mapping of complex network relations to low-dimensional features, on the basis of constructing image semantic concept network, apply deep walk algorithm to learn the potential relationship of nodes in semantic concept network, and combine complex The nodes in the network are mapped into a low-dimensional feature vector, and multinomial logistic regression fuses image and text features to solve visual question answering problems. The invention digs deep into the conceptual co-occurrence mode and the hierarchical structure of the cluster concept, effectively integrates the visual and semantic features of the image, and the natural language features, and provides a feasible way to solve the visual question answering problem.

Description

technical field [0001] The invention relates to a complex network analysis method for solving visual question answering (VQA) problems. The method is a novel solution to open question answering tasks in VQA, and at the same time ensures the accuracy of visual question answering. It belongs to fields of computer vision and natural language processing. Background technique [0002] In recent years, with the rapid development of artificial intelligence, people's demand for intelligence has become more and more diverse. Among them, the visual question answering model, as a cross field between computer vision and natural language processing, has also attracted much attention, but its accuracy rate is far from To achieve user satisfaction business experience. Developing computer vision programs that can answer arbitrary natural language questions about visual images is still considered an ambitious and necessary endeavor. The work combines various subtasks in computer vision, su...

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 Patents(China)
IPC IPC(8): G06K9/46G06K9/62
CPCG06V10/464G06F18/214
Inventor 李群肖甫徐鼎周剑
Owner NANJING UNIV OF POSTS & TELECOMM
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
Eureka Blog
Learn More
PatSnap group products