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A method and system for model determination

A technology for determining methods and models, applied in the field of model determination methods and systems, and can solve problems such as machine learning model adversarial sample confusion

Active Publication Date: 2022-03-11
ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, researchers have found that machine learning models are easily "confuse" by adversarial examples

Method used

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  • A method and system for model determination
  • A method and system for model determination
  • A method and system for model determination

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Embodiment Construction

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings that need to be used in the description of the embodiments. Obviously, the accompanying drawings in the following description are only some examples or embodiments of the present application, and those skilled in the art can also apply the present application to other similar scenarios. Unless otherwise apparent from context or otherwise indicated, like reference numerals in the figures represent like structures or operations.

[0016] It should be understood that "system", "device", "unit" and / or "module" as used herein is a method for distinguishing different components, elements, components, parts or assemblies of different levels. However, the words may be replaced by other expressions if other words can achieve the same purpose.

[0017] As indicated in this application and claims, the terms "a", "an", "an" and / o...

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Abstract

The embodiment of this specification discloses a method for determining a model. The method includes: acquiring a source image and a target image, wherein the source image belongs to a first image category and the target image belongs to a second image category; determining a patch area, the patch area is used to define an adversarial patch to be used for the The position and size in the source image and the target image; based on the source image, the target image and the patch area, through multiple rounds of iterations to determine an adversarial patch, wherein the adversarial patch is used for the target image The obtained adversarial examples can be identified by the machine learning model as belonging to the first image category; using the adversarial examples to perform adversarial training on the machine learning model to obtain a target model.

Description

technical field [0001] The embodiments of this specification relate to the field of machine learning, and in particular to a method and system for determining a model. Background technique [0002] In recent years, image recognition has become an important part of the way for users to generate financial flows or participate in activities. For example, in the face-swiping payment scenario, the recognition of the user's face (including steps such as liveness detection and face image recognition) is often a substitute for identification methods such as passwords, fingerprints or mobile phone verification codes. In real-world payment scenarios, facial recognition payment can greatly reduce the time required for the payment process (you can pay without jumping out of electronic devices such as mobile phones) and improve user experience. Another example is in the reimbursement business, the automatic recognition of the invoice can prompt the user to upload the correct invoice, wh...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V10/764G06V10/70G06N20/00
CPCG06N20/00G06F18/24
Inventor 李慧琛徐晓骏张晓露
Owner ALIPAY (HANGZHOU) INFORMATION TECH CO LTD