Ke depan, potensi AI dalam verifikasi koleksi xylarium mengarah pada masa depan dengan efisiensi dan akurasi yang lebih tinggi, yang dapat mendorong peningkatan signifikan dalam upaya konservasi. Inisiatif kolaboratif dan riset yang berkelanjutan diharapkan dapat terus menyempurnakan aplikasi AI, memperkuat kerja sama internasional, dan mendorong inovasi dalam pengelolaan spesimen botani. Seiring dengan semakin banyaknya lembaga yang mengadopsi teknologi AI, lanskap verifikasi xylarium diprediksi akan mengalami transformasi besar, mendukung tujuan ganda: kemajuan ilmiah dan pelestarian keanekaragaman hayati [6][7].
Referensi
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[6] R. Arévalo et al., “Imaged based identification of colombian timbers using the xylotron: A proof of concept international partnership,” Colomb. For., vol. 24, no. 1, pp. 5–16, 2021.
[7] R. G. H. Rahmanto et al., “Anatomical comparison of branches and trunks of seven commercial wood species,” in IOP Conference Series: Earth and Environmental Science, 2021, vol. 914, no. 1, p. 12071.
[8] P. Ravindran et al., “Field-deployable computer vision wood identification of Peruvian timbers,” Front. Plant Sci., vol. 12, p. 647515, 2021.
[9] M. R. Arifin, B. Sugiarto, R. Wardoyo, Y. Rianto, and others, “Development of mobile-based application for practical wood identification,” in IOP Conference Series: Earth and Environmental Science, 2020, vol. 572, no. 1, p. 12040.
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