| Item type |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2023-02-23 |
| タイトル |
|
|
タイトル |
Spectral Angle Mapping and AI Methods Applied in Automatic Identification of Placer Deposit Magnetite Using Multispectral Camera Mounted on UAV |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
UAV |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
remote sensing |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
hyperspectral imaging |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
multispectral imaging |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
spectral angle mapping |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
artificial intelligence |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
machine learning |
| 主題 |
|
|
主題Scheme |
Other |
|
主題 |
deep learning |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| アクセス権 |
|
|
アクセス権 |
open access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 作成者 |
Sinaice, BrianBino
Owada, Narihiro
Ikeda, Hajime
Toriya, Hisatoshi
Bagai, Zibisani
Shemang, Elisha
Adachi, Tsuyoshi
Kawamura, Youhei
|
| 内容記述 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
The use of drones in mining environments is one way in which data pertaining to the state of a site in various industries can be remotely collected. This paper proposes a combined system that employs a 6-bands multispectral image capturing camera mounted on an Unmanned Aerial Vehicle (UAV) drone, Spectral Angle Mapping (SAM), as well as Artificial Intelligence (AI). Depth possessing multispectral data were captured at different flight elevations. This was in an attempt to find the best elevation where remote identification of magnetite iron sands via the UAV drone specialized in collecting spectral information at a minimum accuracy of +/- 16 nm was possible. Data were analyzed via SAM to deduce the cosine similarity thresholds at each elevation. Using these thresholds, AI algorithms specialized in classifying imagery data were trained and tested to find the best performing model at classifying magnetite iron sand. Considering the post flight logs, the spatial area coverage of 338 m(2), a global classification accuracy of 99.7%, as well the per-class precision of 99.4%, the 20 m flight elevation outputs presented the best performance ratios overall. Thus, the positive outputs of this study suggest viability in a variety of mining and mineral engineering practices. |
|
言語 |
en |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| 書誌情報 |
en : MINERALS
巻 12,
号 2,
発行日 2022
|
| 収録物識別子 |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
2075-163X |
| 出版者 |
|
|
出版者 |
MDPI |
|
言語 |
en |
| 関連情報 |
|
|
関連タイプ |
isIdenticalTo |
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|
識別子タイプ |
DOI |
|
|
関連識別子 |
https://doi.org/10.3390/min12020268 |
| 権利情報 |
|
|
権利情報 |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
kokuA_2022_18.pdf (9.7 MB)
