文献
J-GLOBAL ID:202202289726577025
整理番号:22A0971144
作業者安全性のための個人保護装置の100+FPS検出器:グリーンエッジ計算のための深層学習アプローチ【JST・京大機械翻訳】
100+ FPS detector of personal protective equipment for worker safety: A deep learning approach for green edge computing
著者 (6件):
Ke Xiao
(Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing, College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China)
,
Ke Xiao
(Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, Fuzhou, China)
,
Chen Wenyao
(Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing, College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China)
,
Chen Wenyao
(Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, Fuzhou, China)
,
Guo Wenzhong
(Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing, College of Mathematics and Computer Science, Fuzhou University, Fuzhou, China)
,
Guo Wenzhong
(Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, Fuzhou, China)
資料名:
Peer-to-Peer Networking and Applications
(Peer-to-Peer Networking and Applications)
巻:
15
号:
2
ページ:
950-972
発行年:
2022年
JST資料番号:
W4837A
ISSN:
1936-6450
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
ドイツ (DEU)
言語:
英語 (EN)