开发一个高精度自动识别植物标本系统。
Development of a system for the automated identification of herbarium specimens with high accuracy.
机构信息
Interdisciplinary Faculty of Science and Engineering, Shimane University, 1060 Nishikawatsu, Matsue, Shimane, 690-8504, Japan.
Institute for Natural and Environmental Sciences, University of Hyogo/ Museum of Nature and Human Activities, Hyogo, 6 Chome, Yayoigaoka, Sanda, Hyogo, 669-1546, Japan.
出版信息
Sci Rep. 2022 May 16;12(1):8066. doi: 10.1038/s41598-022-11450-y.
Herbarium specimens are dried plants mounted onto paper. They are used by a limited number of researchers, such as plant taxonomists, as a source of information on morphology and distribution. Recently, digitised herbarium specimens have begun to be used in comprehensive research to address broader issues. However, some specimens have been misidentified, and if used, there is a risk of drawing incorrect conclusions. In this study, we successfully developed a system for identifying taxon names with high accuracy using an image recognition system. We developed a system with an accuracy of 96.4% using 500,554 specimen images of 2171 plant taxa (2064 species, 9 subspecies, 88 varieties, and 10 forms in 192 families) that grow in Japan. We clarified where the artificial intelligence is looking to make decisions, and which taxa is being misidentified. As the system can be applied to digitalised images worldwide, it is useful for selecting and correcting misidentified herbarium specimens.
标本馆标本是固定在纸上的干燥植物。它们仅被少数研究人员使用，例如植物分类学家，作为形态和分布信息的来源。最近，数字化的标本馆标本开始被用于全面研究，以解决更广泛的问题。但是，有些标本被错误识别，如果使用，可能会得出错误的结论。在这项研究中，我们成功地开发了一种使用图像识别系统识别分类群名称的系统，该系统具有很高的准确性。我们使用日本生长的 2171 种植物类群（2064 种、9 亚种、88 变种和 192 个科中的 10 种形式）的 500,554 个标本图像开发了一个准确率为 96.4％的系统。我们明确了人工智能在哪里做出决策，以及哪些分类群被错误识别。由于该系统可以应用于全球的数字化图像，因此对于选择和纠正错误识别的标本馆标本非常有用。
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