Adaptive generation system for image semantic description

A semantic description and self-adaptive technology, applied to instruments, character and pattern recognition, computer components, etc.

Pending Publication Date: 2019-09-06
CHINA UNIV OF MINING & TECH
View PDF4 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of the above analysis, the present invention aims to provide an adaptive generation system for image semantic description, to solve the current image semantic descr

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
  • Adaptive generation system for image semantic description
  • Adaptive generation system for image semantic description
  • Adaptive generation system for image semantic description

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0065] Preferred embodiments of the present invention will be specifically described below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of the application and are used together with the embodiments of the present invention to explain the principle of the present invention, but not to limit the scope of the present invention.

[0066] A specific embodiment of the present invention, such as figure 1 As shown, an adaptive generation system for image semantic description is disclosed, including an image reader 1, an encoder 2, a decoder 3 and a semantic description display 4; the output port of the image reader 1 is connected to the encoding The input port of device 2; The output port of described encoder 2 is connected the input port of described decoder 3; The output port of described decoder 3 is connected the input port of described semantic description display 4;

[0067] The image reader 1 is used to acquire an image to b...

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 an adaptive generation system for image semantic description, and belongs to the technical field of image semantic description. The system comprises an image reader, an encoder, a decoder and a semantic description display. The image reader is used for acquiring an image to be described semantically. The encoder comprises a global feature extraction unit, a local feature extraction unit and an image feature combination unit. The decoder comprises a single-layer or multi-layer neural network. The neural network comprises an LSTM part, an Attention part and an MLP part,and a semantic description model is generated. The Attention part adopts a self-adaptive attention mechanism. The decoder generates words and sentences of image semantic description by utilizing the semantic description model according to the combination information output by the encoder. The semantic description display is used for outputting and displaying words and phrases of the image semanticdescription. The focus key point of the image is determined, higher-level semantic information is mined, and the detail information problem describing words or sentences is perfected.

Description

technical field [0001] The invention relates to the technical field of image semantic description, in particular to an adaptive generation system for image semantic description. Background technique [0002] With the rapid development of artificial intelligence and breakthroughs in deep learning technology, computer vision technology based on deep learning is becoming more and more mature. Researchers are trying to make machines understand more complex semantic information in visual information. Therefore, at the intersection of computer vision and natural language processing The research direction of image semantic description appears in the field. The image semantic description technology was first proposed by Farhadi et al. Its goal is to realize the transformation from the image in the visual space to the text description in the semantic space. The method realizes the mapping from the image to the text description sentence, and gives semantic interpretation to the visual...

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): G06K9/46G06K9/48G06K9/62
CPCG06V10/469G06V10/44G06F18/253
Inventor 赵小虎有鹏尹良飞李祎宸刘勇
Owner CHINA UNIV OF MINING & TECH
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