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METHOD OF CLASSIFICATION OF IMAGES AMONG DIFFERENT CLASSES

机译:不同类别图像的分类方法

摘要

This invention relates to a method of classification of images among different classes comprising: performing a dimensionality reduction step for said different classes on a training set of images whose classes are known, and then classifying one or more unknown images among said different classes with reduced dimensionality, said dimensionality reduction step being performed on said training set of images by machine learning including processing, for at least a first matrix and for at least a second matrix, a parameter representative of a product of two first and second matrices to assess to which given classes several first given images respectively belong: first matrix representing the concatenation, for said several first given images, of the values of the pixels of each said first given image, second matrix representing the concatenation, for said several first given images, of the values of differences between the pixels of each said first given image and the pixels of a second given image different from said first given image but known to belong to same class as said first given image, wherein: a quantum singular value estimation is performed on first matrix, a quantum singular value estimation is performed on second matrix, both quantum singular value estimation of first matrix and quantum singular value estimation of second matrix are combined together, via quantum calculation, so as to get at a quantum singular value estimation of said product of both first and second matrices, said quantum singular value estimation of said product of both first and second matrices being said parameter representative of said product of two first and second matrices processed to assess to which given classes said several first given images respectively belong.
机译:本发明涉及一种在不同类别之间对图像进行分类的方法,该方法包括:在其类别已知的训练图像集上针对所述不同类别执行降维步骤,然后在所述不同类别中以降维对一个或多个未知图像进行分类。 ,所述降维步骤是通过机器学习对所述图像训练集执行的,包括对至少第一矩阵和至少第二矩阵处理代表两个第一和第二矩阵的乘积的参数以评估给定哪个类分别属于几个第一给定图像:对于所述多个第一给定图像,第一矩阵代表每个所述第一给定图像的像素值的级联;对于所述多个第一给定图像,第二矩阵代表所述值的串联每个所述第一给定图像的像素与第二g图像的像素之间的差异与所述第一给定图像不同但已知与所述第一给定图像属于同一类别的图像,其中:对第一矩阵执行量子奇异值估计,对第二矩阵执行量子奇异值估计,这两个量子奇异值估计经由量子计算,将第一矩阵的乘积和第二矩阵的量子奇异值估计组合在一起,以获得第一和第二矩阵的所述乘积的量子奇异值估计,第一矩阵和第二矩阵的乘积的所述量子奇异值估计第二矩阵是代表两个第一和第二矩阵的乘积的所述参数的参数,该两个第一和第二矩阵经过处理以评估所述多个第一给定图像分别属于哪个给定类别。

著录项

  • 公开/公告号US2020210755A1

    专利类型

  • 公开/公告日2020-07-02

    原文格式PDF

  • 申请/专利权人 BULL SAS;

    申请/专利号US201916728517

  • 发明设计人 ALESSANDRO LUONGO;

    申请日2019-12-27

  • 分类号G06K9/62;G06N20;G06N10;G06F17/14;

  • 国家 US

  • 入库时间 2022-08-21 11:21:51

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