In this study, we investigated the possibility of using an artificial neural network (ANN) to classify human hair samples according to pigment (original or bleached hair) and sex (female or male) from numerical data obtained by wavelength dispersive X‐ray fluorescence (WDXRF) and by laser‐induced breakdown spectroscopy (LIBS). The results were promising, showing that the developed ANNs are able to classify the pigment and donor sex of hair samples with 100% and 89.5% accuracy, respectively, in the test set using WDXRF data. For the LIBS data in the test set, 100% of the pigment classifications were correct, and 78.9% of the donor sex classifications were correct.

中文翻译：

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使用无创分析技术将人工神经网络应用于根据色素和性别对头发样本进行分类

在这项研究中，我们研究了使用人工神经网络（ANN）根据色散（原始或漂白的头发）和性别（女性或男性）根据波长色散X射线荧光获得的数值数据对人类头发样本进行分类的可能性（ WDXRF）和激光诱导击穿光谱（LIBS）。结果令人鼓舞，表明开发的人工神经网络能够在使用WDXRF数据的测试集中，分别以100％和89.5％的准确度对头发样本的色素和供体性别进行分类。对于测试集中的LIBS数据，正确的颜料分类为100％，正确的供体性别分类为78.9％。