文献
J-GLOBAL ID:202102268798492112
整理番号:21A3170400
環境懸念の有機化学物質を認識するための深い畳込みニューラルネットワークプロセスのより良い理解に向けて【JST・京大機械翻訳】
Towards a better understanding of deep convolutional neural network processes for recognizing organic chemicals of environmental concern
著者 (7件):
Sun Xiangfei
(Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 511443, China)
,
Zhang Xianming
(Department of Chemistry and Biochemistry, Concordia University, Montreal, Quebec H4B 1R6, Canada)
,
Wang Luyao
(Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 511443, China)
,
Li Yuanxin
(Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 511443, China)
,
Muir Derek C.G.
(Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 511443, China)
,
Muir Derek C.G.
(Environment and Climate Change Canada, Aquatic Contaminants Research Division, 867 Lakeshore Road, Burlington, Ontario L7S 1A1, Canada)
,
Zeng Eddy Y.
(Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou 511443, China)
資料名:
Journal of Hazardous Materials
(Journal of Hazardous Materials)
巻:
421
ページ:
Null
発行年:
2022年
JST資料番号:
B0362A
ISSN:
0304-3894
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)