A wealth of forensic wood identification technologies has been developed or improved in recent years, with many attempts to compare results between technologies. The utility of such comparisons is greatly reduced when the species tested with each technology are different and when performance metrics are not calculated or presented in the same way. Here, a species-level XyloTron computer vision model is presented along with a side-by-side comparison for species- and genus-level identification of the 10 species of Meliaceae studied by Deklerck et al. using mass spectrometry. The species-level accuracies of the XyloTron model and the mass spectrometry models are comparable, while the genus-level accuracy of the XyloTron model is higher than that of the mass spectrometry model. The paper concludes with a call for better practices to compare disparate forensic wood identification technologies from a performance driven perspective.

中文翻译：

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十种楝科木材的两种法医木材鉴定技术比较：计算机视觉与质谱法

近年来，已经开发或改进了大量法医木材识别技术，并多次尝试比较技术之间的结果。当使用每种技术测试的物种不同并且性能指标的计算或呈现方式不同时，这种比较的效用会大大降低。在这里，提出了一个物种级 XyloTron 计算机视觉模型，同时对 Deklerck 等人研究的 10 种楝科植物的物种和属级鉴定进行了并排比较。使用质谱法。XyloTron 模型的种级精度与质谱模型相当，而 XyloTron 模型的属级精度高于质谱模型。