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

An ore sorting method based on a convolutional neural network

A convolutional neural network and ore technology, applied in the field of sorting, can solve problems such as low accuracy and low efficiency, and achieve the effects of improving accuracy, improving economic benefits, and improving accuracy

Inactive Publication Date: 2019-05-10
HUAQIAO UNIVERSITY
View PDF7 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is to provide a method for ore sorting based on convolutional neural network, which can effectively solve the problems of low efficiency and low accuracy caused by manual classification in the prior art

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
  • An ore sorting method based on a convolutional neural network
  • An ore sorting method based on a convolutional neural network
  • An ore sorting method based on a convolutional neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0048] Please refer to Figure 1 to Figure 3 Shown, a kind of preferred embodiment of the ore sorting method based on convolution neural network of the present invention, described method comprises the steps:

[0049] Step S1, making a training set and a test set of ore pictures;

[0050] In a specific embodiment of the present invention, the step S1 specifically includes:

[0051] Step S11. Under the same environment, use the same shooting instrument to shoot the collected ores of different qualities to obtain various ore pictures; in actual implementation, it is necessary to collect as many ore pictures as possible to ensure sufficient data sources. The purpose of shooting in the same environment and with the same shooting equipment is to reduce the interference of the surrounding environment on the ore pictures taken. The shooting instrument can be selected as a gray point color camera of FL3-GE-03S1M-C for shooting, and the pixel size is 1024×1280. Of course, the present...

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 provides an ore sorting method based on a convolutional neural network. The method comprises the following steps: making a training set and a test set of ore pictures; building VGG-SE model for inputting the ore pictures in the training set into the VGG-SE model and using VGG-SE model to carry out feature extraction on the ore picture to obtain a group of feature vectors; inputting agroup of obtained feature vectors into a softmax classifier, and classifying the ore pictures through the softmax classifier to obtain a trained VGG-SE model; inputting ore pictures in a test set toa trained VGG-SE modle to perform prediction to obtain a prediction result. The method has the advantages that compared with existing manual classification, machine classification is used for replacing manual classification, the classification accuracy is greatly improved, and meanwhile economic benefits are improved.

Description

technical field [0001] The invention relates to a sorting method, in particular to an ore sorting method based on a convolutional neural network. Background technique [0002] Mineral resources are non-renewable resources. With the massive development of mineral resources, mineral resources are gradually decreasing. This makes the mining industry begin to pay attention to the sorting of ores, which can ensure the utilization of high-quality mineral resources as much as possible in the limited mineral resources. But for now, the sorting of ores mainly relies on manual sorting. Due to the influence of human subjective factors, human eyes are prone to fatigue and other reasons, the sorting rate of ores has always been relatively low, which also directly affects economic benefits. [0003] With the continuous advancement of science and technology, the use of artificial intelligence to solve practical industrial problems has begun to appear widely in recent years. As a branch o...

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): G06K9/62G06K9/00
Inventor 郑力新谢炜芳邱德府
Owner HUAQIAO 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