首页> 外国专利> PLATFORM FOR PREVENTING ADVERSARIAL ATTACKS ON IMAGE-BASED MACHINE LEARNING MODELS

PLATFORM FOR PREVENTING ADVERSARIAL ATTACKS ON IMAGE-BASED MACHINE LEARNING MODELS

机译:防止基于图像的机器学习模型出现攻击性的平台

摘要

Methods, systems, and computer-readable storage media for receiving a set of training images and a set of classification labels, generating a set of target codebooks based on the set of classification labels, the set of target codebooks being provided as a first set of vectors of random value and dimension, generating a set of output codebooks based on the set of training images, the set of output codebooks being provided as a second set of vectors of random value and dimension, training a ML model by minimizing a loss function provided as a mean-squared-error (MSE) loss function, the loss function being measured by the Euclidean distance between an output codebook of the set of output codebooks and a target codebook of the set of target codebooks.
机译:方法,系统和计算机可读存储介质,用于接收一组训练图像和一组分类标签,基于该组分类标签生成一组目标代码簿,该组目标代码簿被提供为第一组随机值和维度的向量,基于训练图像集生成一组输出代码簿,该组输出代码簿作为第二组随机值和维度向量提供,通过最小化提供的损失函数来训练ML模型作为均方误差(MSE)损失函数,该损失函数由一组输出代码簿的输出代码簿与目标代码簿集合的目标代码簿之间的欧几里得距离测量。

著录项

  • 公开/公告号US2020151505A1

    专利类型

  • 公开/公告日2020-05-14

    原文格式PDF

  • 申请/专利权人 SAP SE;

    申请/专利号US201816186784

  • 发明设计人 SEAN SAITO;SUJOY ROY;

    申请日2018-11-12

  • 分类号G06K9/62;G06K9/40;

  • 国家 US

  • 入库时间 2022-08-21 11:24:57

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