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Comparison of two forensic wood identification technologies for ten Meliaceae woods: computer vision versus mass spectrometry

机译:两种法医学木材识别技术的比较:电脑视觉与质谱

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摘要

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.
机译:近年来,已经开发或改善了丰富的法医识别技术,许多试图比较技术之间的结果。当用各自技术测试的物种不同以及以相同方式计算或呈现性能度量时,这种比较的效用大大减少。这里,提出了一种物种级别的XILOTRON计算机视觉模型以及由Deklerck等人研究的10种Meliaceae的物种和属级鉴定的并排比较。使用质谱。木质型模型的物质级精度和质谱型号可比较,而木炭模型的基本级精度高于质谱模型的基本精度。本文结束了呼吁,以便更好地比较不同的法证木材识别技术从性能驱动的角度比较。

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  • 来源
    《Wood Science and Technology》 |2020年第5期|1139-1150|共12页
  • 作者单位

    Univ Wisconsin Dept Bot Madison WI 53706 USA;

    Univ Wisconsin Dept Bot Madison WI 53706 USA|US Forest Serv Forest Prod Lab Ctr Wood Anat Res USDA Madison WI 53726 USA|Purdue Univ Dept Forestry & Nat Resources W Lafayette IN 47907 USA|Univ Estadual Paulista Botucatu Ciencias Biol Bot Sao Paulo Brazil;

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