文献
J-GLOBAL ID:202002229252198650
整理番号:20A1495786
UAVベースマルチスペクトル画像を用いたバナナ萎凋病を同定するためのサポートベクトルマシン,人工ニューラルネットワークおよびランダムフォレストの性能【JST・京大機械翻訳】
Performance of Support Vector Machines, Artificial Neural Network, and Random Forest for Identifying Banana Fusarium Wilt Using UAV-Based Multi-spectral Imagery
著者 (13件):
Ye Huichun
(Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China)
,
Ye Huichun
(Key Laboratory of Earth Observation, Sanya, Hainan, China)
,
Cui Bei
(Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China)
,
Cui Bei
(Key Laboratory of Earth Observation, Sanya, Hainan, China)
,
Huang Shanyu
(Chinese Academy of Agricultural Engineering Planning and Design, Beijing, China)
,
Dong Yingying
(Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China)
,
Huang Wenjiang
(Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China)
,
Huang Wenjiang
(Key Laboratory of Earth Observation, Sanya, Hainan, China)
,
Guo Anting
(Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China)
,
Guo Anting
(University of Chinese Academy of Sciences, Beijing, China)
,
Ren Yu
(Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China)
,
Ren Yu
(University of Chinese Academy of Sciences, Beijing, China)
,
Jin Yu
(School of Electronics and Information Engineering, Anhui University, Hefei, China)
資料名:
Lecture Notes in Electrical Engineering
(Lecture Notes in Electrical Engineering)
巻:
657
ページ:
261-270
発行年:
2020年
JST資料番号:
W5070A
ISSN:
1876-1100
資料種別:
会議録 (C)
記事区分:
原著論文
発行国:
ドイツ (DEU)
言語:
英語 (EN)