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Face scanning examination method based on convolutional neural network

A convolutional neural network, face information technology, applied in biological neural network models, neural architectures, instruments, etc., to achieve the effect of ensuring fairness

Inactive Publication Date: 2021-08-24
吴柯磊
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For the rapid development of online examinations, traditional methods such as manual proctoring and fingerprint verification can no longer meet the needs of online examinations. In order to ensure the fairness and impartiality of examinations, researchers need to vigorously develop computer monitoring technology and use information monitoring to assist network examinations. system operation

Method used

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Examples

Experimental program
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Embodiment Construction

[0027] The present invention will be described in further detail below through examples, and the following examples are explanations of the present invention and the present invention is not limited to the following examples.

[0028] Embodiments of the present invention include the following steps:

[0029] (1) Enter face information;

[0030] (2) Select the data set;

[0031] (3) Divide the data set into training data, verification data and test data;

[0032] (4) Preprocessing the data;

[0033] (5) Read the picture by loading the PIL module;

[0034] (6) Use numpy.asarray to normalize the data;

[0035] (7) Load the pickle module;

[0036] (8) Build a model; this step includes the following steps:

[0037] 1) Establish a Sequential linear stacking model of keras;

[0038] 2) Establish the first convolutional layer;

[0039] 3) Establish the first pooling layer;

[0040] 4) Create a second convolutional layer;

[0041] 5) Establish a second pooling layer;

[0042...

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Abstract

Provided is a face scanning examination method based on a convolutional neural network. Accurate verification of examinee identities in a large-scale examination is realized, and the fairness of examination is guaranteed. The method comprises the following steps: (1) inputting face information; (2) selecting a data set; (3) dividing the data set into training data, verification data and test data; (4) preprocessing the data; (5) reading a picture by loading a PIL module; (6) carrying out normalization processing on the data; (7) loading a pickle module; (8) establishing a model; and (9) completing identification.

Description

technical field [0001] The invention relates to a face-scanning examination method based on a convolutional neural network. Background technique [0002] At present, most of the examinations in our country still use traditional identity verification methods, which include manual verification of ID cards and machine fingerprint recognition. [0003] Manual verification of ID card is a very traditional identification method. It only needs the invigilator to compare the appearance of the candidate with the photo on the ID card. The inspection is simple, easy to operate, and low in cost. However, some examinees can find "gunmen" to take the exam by falsifying their documents, so this traditional method has loopholes for cheating. In addition, the photo taking time of the candidate's ID card is not at the same time as the test time, which may lead to differences between the photo on the candidate's ID card and the candidate's own appearance, making the candidate's identity verif...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06F21/32G06N3/04
CPCG06F21/32G06V40/161G06V40/168G06N3/045G06F18/214
Inventor 吴柯磊王璇宁静瑶朱忆怡叶宸源
Owner 吴柯磊
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