文献
J-GLOBAL ID:202202283442137570
整理番号:22A0287588
ハイブリッドチャネル特徴損失を有するCNNに基づく二重偏波SAR船舶粒度分類【JST・京大機械翻訳】
Dual-Polarized SAR Ship Grained Classification Based on CNN With Hybrid Channel Feature Loss
著者 (7件):
Zeng Liang
(Department of Electronic Engineering, Tsinghua University, Beijing, China)
,
Zhu Qingtao
(Department of Electronic Engineering, Tsinghua University, Beijing, China)
,
Lu Danwei
(Department of Electronic Engineering, Tsinghua University, Beijing, China)
,
Zhang Tao
(Department of Electronic Engineering, Tsinghua University, Beijing, China)
,
Wang Hongmiao
(Department of Electronic Engineering, Tsinghua University, Beijing, China)
,
Yin Junjun
(Department of Electronic Engineering, Tsinghua University, Beijing, China)
,
Yang Jian
(Department of Electronic Engineering, Tsinghua University, Beijing, China)
資料名:
IEEE Geoscience and Remote Sensing Letters
(IEEE Geoscience and Remote Sensing Letters)
巻:
19
ページ:
ROMBUNNO.4011905.1-5
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)