Mobile phone model identification method based on convolutional neural network

A convolutional neural network and identification method technology, applied in the field of solid waste treatment, to achieve the effect of rapid and accurate identification, improved accuracy and rapidity, and improved efficiency

Pending Publication Date: 2019-12-13
BEIJING UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0006] The present invention obtains a method for identifying the model of a waste mobile phone based on a convolutional neural network. The recognition method extracts the identifiable mobile phone area in the inspection photo through an edge detection algorithm, and uses the convolutional neural network to realize fast and accurate identification of the model of a waste mobile phone. Identification; solves the problem of model identification in the recycling process of waste mobile phones, and improves the recycling efficiency of mobile phones

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  • Mobile phone model identification method based on convolutional neural network
  • Mobile phone model identification method based on convolutional neural network
  • Mobile phone model identification method based on convolutional neural network

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Embodiment Construction

[0040] 1. a mobile phone model identification method based on convolutional neural network, is characterized in that, comprises the following steps:

[0041] (1) Design a mobile phone image preprocessing method based on edge detection algorithm

[0042] ①Convert the inspection photo containing the image of the back of the mobile phone into a single-channel grayscale image. The grayscale conversion formula is as follows:

[0043] p G (x,y)=αp r (x,y)+βp g (x,y)+γp b (x,y); (10)

[0044] Among them, p G (x, y) represents the pixel value of the point (x, y) in the image after grayscale, p r (x, y) represents the pixel value of the red channel of point (x, y), p g (x, y) represents the pixel value of the green channel of point (x, y), p b (x, y) represents the pixel value of the blue channel of the point (x, y), α is the gray-scale reconciliation weight of the r channel, α=0.299; β is the gray-scale reconciliation weight of the g channel, β=0.588; γ is b Channel grayscale...

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Abstract

The invention provides a waste mobile phone model identification method based on a convolutional neural network. The problem that in the waste mobile phone recycling process, a model is difficult to accurately identify is solved. According to the invention, an edge detection algorithm is used to analyze regional features in a mobile phone verification picture; a feature extraction convolutional network sharing the weight is constructed. The similarity between the image area features of the waste mobile phone and the standard sample is evaluated, rapid identification of the mobile phone model is realized, the mobile phone model identification in different scenes maintains good rapidity and accuracy, and the recovery efficiency of the waste mobile phone and the economic benefit of a recoveryenterprise can be improved.

Description

technical field [0001] The invention utilizes the model recognition method of the used mobile phone based on the convolutional neural network to realize the accurate identification of the model of the mobile phone in the recycling process of the used mobile phone. In the process of recycling waste mobile phones, it is possible to obtain greater economic benefits by classifying mobile phones by model. The identification of mobile phone models has become an important factor affecting the efficiency of waste mobile phone recycling. There are many brands and models of mobile phones with high similarity, so it is necessary to have a certain Only with the accumulation of experience can we skillfully distinguish between mobile phone models. Applying the convolutional neural network-based model identification method of used mobile phones to the recycling process of used mobile phones can avoid problems such as classification errors and low classification efficiency caused by inexperie...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/10G06V10/44G06N3/045G06F18/241
Inventor 韩红桂甄琪张璐伍小龙
Owner BEIJING UNIV OF TECH
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