文献
J-GLOBAL ID:202002217392186974
整理番号:20A1750879
NAS-FCOS:オブジェクト検出のための高速ニューラルアーキテクチャ探索【JST・京大機械翻訳】
NAS-FCOS: Fast Neural Architecture Search for Object Detection
著者 (7件):
Wang Ning
(School of Computer Science, Northwestern Polytechnical University, China; National Engineering Lab for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, China)
,
Gao Yang
(School of Computer Science, Northwestern Polytechnical University, China; National Engineering Lab for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, China)
,
Chen Hao
(The University of Adelaide, Australia)
,
Wang Peng
(School of Computer Science, Northwestern Polytechnical University, China; National Engineering Lab for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, China)
,
Tian Zhi
(The University of Adelaide, Australia)
,
Shen Chunhua
(The University of Adelaide, Australia)
,
Zhang Yanning
(School of Computer Science, Northwestern Polytechnical University, China; National Engineering Lab for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, China)
資料名:
IEEE Conference Proceedings
(IEEE Conference Proceedings)
巻:
2020
号:
CVPR
ページ:
11940-11948
発行年:
2020年
JST資料番号:
W2441A
資料種別:
会議録 (C)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)