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Authenticity of objects using machine learning from microscopic differences

机译:利用机器学习从微观差异中获取物体的真实性

摘要

A method for classifying a microscopic image includes receiving a training dataset (306) including at least one microscopic image (305) from a physical object (303) and an associated class definition (304) for the image that is based on a product specification. Machine learning classifiers are trained to classify the image into classes (308). The microscopic image (305) is used as a test input for the classifiers to classify the image into one or more classes based on the product specification. The product specification includes a name of a brand, a product line, or other details on a label of the physical object.
机译:一种用于对微观图像进行分类的方法,包括:从物理对象(303)接收训练数据集(306),该训练数据集(306)包括至少一个微观图像(305);以及基于产品规格的图像的相关联的类别定义(304)。训练机器学习分类器以将图像分类为类(308)。显微图像(305)用作分类器的测试输入,以基于产品规格将图像分类为一个或多个类别。产品规格在物理对象的标签上包括品牌名称,产品系列或其他详细信息。

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