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METHOD FOR CHARACTERISING SAMPLES USING NEURAL NETWORKS

机译:用神经网络表征样品的方法

摘要

A method for characterizing a sample using spectral images of the sample. At least one volume of values of an observed parameter is generated from the images for a plurality of coordinates of the pixels of the images and a plurality of acquisitions. At least one set of input data from the volume is extracted, with the input data corresponding to the values of the parameter, for a pixel of given coordinates in various acquisitions, to which values at least one conversion function has been applied. The at least one neural network is trained using the input data in order to extract therefrom at least one feature of the sample to be characterized. The at least one feature extracted by the neural network is used to perform a classification of the input data into a plurality of classes, each class being representative of at least one feature of the sample.
机译:一种使用样品的光谱图像表征样品的方法。对于图像的像素的多个坐标和多个采集,从图像产生至少一个体积的观测参数值。对于各种采集中给定坐标的像素,从体积中提取至少一组输入数据,其中输入数据与参数的值相对应,该值已应用了至少一个转换函数。使用输入数据来训练至少一个神经网络,以便从中提取待表征的样本的至少一个特征。由神经网络提取的至少一个特征被用于将输入数据分类为多个类别,每个类别代表样本的至少一个特征。

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