دورية أكاديمية
Opening the black box: explainable deep-learning classification of wood microscopic image of endangered tree species
| العنوان: | Opening the black box: explainable deep-learning classification of wood microscopic image of endangered tree species |
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| المؤلفون: | Chang Zheng, Shoujia Liu, Jiajun Wang, Yang Lu, Lingyu Ma, Lichao Jiao, Juan Guo, Yafang Yin, Tuo He |
| المصدر: | Plant Methods, Vol 20, Iss 1, Pp 1-11 (2024) |
| بيانات النشر: | BMC, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Plant culture LCC:Biology (General) |
| مصطلحات موضوعية: | Computer vision, Deep learning, Feature visualization, Image classification, Wood identification, Plant culture, SB1-1110, Biology (General), QH301-705.5 |
| الوصف: | Abstract Background Traditional method of wood species identification involves the use of hand lens by wood anatomists, which is a time-consuming method that usually identifies only at the genetic level. Computer vision method can achieve "species" level identification but cannot provide an explanation on what features are used for the identification. Thus, in this study, we used computer vision methods coupled with deep learning to reveal interspecific differences between closely related tree species. Result A total of 850 images were collected from the cross and tangential sections of 15 wood species. These images were used to construct a deep-learning model to discriminate wood species, and a classification accuracy of 99.3% was obtained. The key features between species in machine identification were targeted by feature visualization methods, mainly the axial parenchyma arrangements and vessel in cross section and the wood ray in tangential section. Moreover, the degree of importance of the vessels of different tree species in the cross-section images was determined by the manual feature labeling method. The results showed that vessels play an important role in the identification of Dalbergia, Pterocarpus, Swartzia, Carapa, and Cedrela, but exhibited limited resolutions on discriminating Swietenia species. Conclusion The research results provide a computer-assisted tool for identifying endangered tree species in laboratory scenarios, which can be used to combat illegal logging and related trade and contribute to the implementation of CITES convention and the conservation of global biodiversity. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1746-4811 |
| Relation: | https://doaj.org/toc/1746-4811 |
| DOI: | 10.1186/s13007-024-01191-6 |
| URL الوصول: | https://doaj.org/article/7e45c345971e44f3a00a70a4eb5ce0a5 |
| رقم الأكسشن: | edsdoj.7e45c345971e44f3a00a70a4eb5ce0a5 |
| قاعدة البيانات: | Directory of Open Access Journals |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 17464811 |
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| DOI: | 10.1186/s13007-024-01191-6 |