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Enhanced training method and device for image recognition model

An image recognition and training method technology, applied in the computer field, can solve the problems such as the inability to guarantee the security of funds in the face payment authentication business scenario, the reduction of the accuracy of the image recognition result, etc., to achieve the effect of good recognition function and improved robustness

Active Publication Date: 2020-12-18
ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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AI Technical Summary

Problems solved by technology

[0003] In this case, if the image recognition model only uses standard training samples for training, the accuracy of the image recognition results may be reduced in the case of increased image interference, causing certain troubles, such as face payment authentication business scenarios. Fund security cannot be guaranteed

Method used

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  • Enhanced training method and device for image recognition model
  • Enhanced training method and device for image recognition model
  • Enhanced training method and device for image recognition model

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Embodiment Construction

[0047] The solutions provided in this specification will be described below in conjunction with the accompanying drawings.

[0048] First, combine figure 1 A specific implementation scenario shown will be described. like figure 1 Shown is a specific implementation scenario of face recognition. In this implementation scenario, firstly, the image recognition model is trained through the first computing platform. The first computing platform can use a large number of face images as training samples to train an image recognition model. Wherein, the face image sample may correspond to at least one of the labeling results of the human face contour labeling result, the living body labeling result, etc., and is used to guide the output result of the image recognition model. The image recognition model can be realized by, for example, a convolutional neural network (CNN). The training process of the image recognition model can be carried out in any suitable conventional way (such ...

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Abstract

The embodiment of the invention provides an enhanced training method for an image recognition model, and the method comprises the steps of randomly selecting a preset number or a preset proportion ofsamples from a first sample set as seed samples, carrying out the extension, and obtaining a plurality of extended samples, wherein disturbance is added to the extended sample on the basis of the original image, and the labeling result is not changed. In a sample expansion process, disturbance values are distributed around in a predetermined manner by taking the reference pixel as a reference, sothat real disturbance can be well simulated. Since the annotation result of the extended sample is not changed after disturbance is added, the image recognition model trained by the extended sample can well recognize the target recognition result of the original image, thereby improving the robustness of the image recognition model.

Description

technical field [0001] One or more embodiments of this specification relate to the field of computer technology, and in particular to methods and devices for image perturbation processing, image sample expansion, and enhanced training of image recognition models using expanded samples. Background technique [0002] Image recognition refers to the technology of using computers to process, analyze and understand images to identify targets and objects in various patterns. Image recognition is widely used in many fields, such as unmanned driving, attendance, payment authentication, criminal investigation and tracking, etc. Among them, in some business scenarios, in addition to target detection, it is also necessary to identify whether the relevant target is a real target entity. For example, in the face payment authentication scenario, considering the security of user funds, in order to avoid using face photos to pretend to be real people for payment , it is also necessary to d...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06T5/00G06N3/04G06N3/08G06Q20/40
CPCG06Q20/40145G06N3/08G06T2207/10004G06T2207/20081G06T2207/20084G06T2207/20221G06T2207/30201G06V40/166G06V40/161G06V40/45G06N3/045G06T5/92G06N20/00G06V40/172G06N5/04G06F18/214G06F18/22G06F18/251
Inventor 徐文浩
Owner ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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