Analysis of the feasibility of using deep learning for multiclass classification of dental anomalies on panoramic radiographs
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この文献の参照には次のURLをご利用ください : https://ir.lib.hiroshima-u.ac.jp/00055587
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Title ( eng ) |
Analysis of the feasibility of using deep learning for multiclass classification of dental anomalies on panoramic radiographs
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Title ( jpn ) |
深層学習によるパノラマエックス線画像からの歯数異常の多値分類
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Creator |
Okazaki Shota
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Language |
eng
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Resource Type | doctoral thesis |
Rights |
© by author, The copyright of this paper belongs to the Japanese Society for Dental Materials and Devices.
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Access Rights | open access |
Source Identifier |
Dental Materials Journal 2022 Volume 41 Issue 6 Pages 889-895
[DOI] https://doi.org/10.4012/dmj.2022-098
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Dissertation Number | 甲第9586号 |
Degree Name | |
Date of Granted | 2024-03-23 |
Degree Grantors |
広島大学
Hiroshima University
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