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

Fine-grained image classification model processing method and device

A classification model and processing method technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problems of low accuracy of classification results, large amount of system calculation, etc., to reduce the distance between classes and increase the distance between classes , the effect of increasing the distance between classes

Pending Publication Date: 2020-11-13
PING AN TECH (SHENZHEN) CO LTD
View PDF1 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, in the technical solution disclosed in the above patent, the system has a large amount of computation, and the accuracy of the improved classification results is low

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
  • Fine-grained image classification model processing method and device
  • Fine-grained image classification model processing method and device
  • Fine-grained image classification model processing method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0045] One of the core ideas of the embodiments of the present invention is to force the model to learn more subtle features between classes by adding a new Euler confusion term to the cross-entropy loss, and realize increasing the distance between classes and shrinking classes end-to-end. At the same time, by adding an identical and shared weight branch to the traditional model, and randomly sorting each first data twice, the new Siamese network can efficiently calculate Euler confusion. The method proposed in the present invention can reduce the class distance and increase the intra-class distance, so that the fine-grained image classification model can improve the performance of fine-grained image classification, and is widely u...

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 embodiment of the invention provides a fine-grained image classification model processing method, and relates to the technical field of image classification. The fine-grained image classificationmodel processing method comprises the steps of generating first data comprising at least two samples according to an obtained data set; processing sample sorting of the first data according to a preset rule to obtain at least two groups of second data; extracting a sample of the second data according to a preset rule to form a sample pair; processing the sample pair through a preset Euler model toobtain a data loss value; and processing a preset first fine-grained image classification model according to the data loss value to obtain a second fine-grained image classification model. Accordingto the invention, the class spacing can be reduced and the intra-class distance can be increased, so that the fine-grained image classification model can improve the fine-grained image classificationperformance.

Description

technical field [0001] The invention relates to the technical field of image classification, in particular to a fine-grained image classification model processing method and a fine-grained image classification model processing device. Background technique [0002] As a classic, fundamental and challenging problem in computer vision, fine-grained image classification has been an active area of ​​research for decades. The goal of fine-grained image classification is to retrieve and identify images of different subcategories under the same broad category (ie metacategory). For example, different genera of animals / plants, different models of cars, different kinds of retail products, etc. [0003] The Chinese patent publication number is CN109800754A, a method for classifying ancient fonts based on convolutional neural networks, which involves the use of the center loss function and the traditional cross-entropy loss function in conjunction with the objective function of the cla...

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): G06K9/62
CPCG06F18/24G06F18/214
Inventor 林春伟刘莉红刘玉宇
Owner PING AN TECH (SHENZHEN) CO LTD
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