文献
J-GLOBAL ID:202202258072682941
整理番号:22A0482672
合成開口レーダ画像からの船舶検出のためのハイパーパラメータ構成学習【JST・京大機械翻訳】
Hyperparameter Configuration Learning for Ship Detection From Synthetic Aperture Radar Images
著者 (5件):
Xu Nuo
(National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences and School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China)
,
Huo Chunlei
(National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences and School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China)
,
Zhang Xin
(National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences and School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China)
,
Cao Yong
(National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences and School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China)
,
Pan Chunhong
(National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences and School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China)
資料名:
IEEE Geoscience and Remote Sensing Letters
(IEEE Geoscience and Remote Sensing Letters)
巻:
19
ページ:
ROMBUNNO.4502805.1-5
発行年:
2022年
JST資料番号:
W1397A
ISSN:
1545-598X
CODEN:
IGRSBY
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)