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  1. Journal Article

Validation study on the practical accuracy of wood species identification via deep learning from visible microscopic images

https://repository.ffpri.go.jp/records/2004550
https://repository.ffpri.go.jp/records/2004550
e17d7f73-553a-4008-b1e9-4b28280f1600
Item type デフォルトアイテムタイプ(シンプル)_学術雑誌論文(1)
Title
Title Validation study on the practical accuracy of wood species identification via deep learning from visible microscopic images
Language en
Creator Ma Te

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en Ma Te

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Kimura Fumiya

× Kimura Fumiya

en Kimura Fumiya

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Tsuchikawa Satoru

× Tsuchikawa Satoru

en Tsuchikawa Satoru

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Kojima Miho

× Kojima Miho

en Kojima Miho

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Inagaki Tetsuya

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en Inagaki Tetsuya

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Keyword
Subject Wood species identification, Microscopic cross-sectional images, Convolutional neural networks (CNN), Practical accuracy, Interactive platform, Web-based identification
Publisher
Publisher NC State University
Language
Language eng
Resource Type
Resource Type(Simple) journal article
Relation
Identifier Type DOI
Related Identifier https://doi.org/10.15376/biores.19.3.4838-4851
Source Identifier
Source Identifier Type EISSN
Source Identifier 1930-2126
Bibliographic Information en : BioResources

Volume Number 19, Issue Number 3, p. 4838-4851, Issue Date 2024-05-31
Reference Number
FR2024-06-09
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