中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Deep learning for track recognition in pixel and strip-based particle detectors

文献类型:期刊论文

作者Bakina, O; Baranov, D; Denisenko, I; Goncharov, P; Nechaevskiy, A; Nefedov, Y; Nikolskaya, A; Ososkov, G; Rusov, D; Shchavelev, E
刊名JOURNAL OF INSTRUMENTATION
出版日期2022
卷号17期号:12页码:P12023
DOI10.1088/1748-0221/17/12/P12023
文献子类Article
会议地点Pattern recognition; cluster finding; calibration and fitting methods; Performance of High Energy Physics Detectors
电子版国际标准刊号1748-0221
语种英语
WOS记录号WOS:000906931400005
源URL[http://ir.ihep.ac.cn/handle/311005/299710]  
专题高能物理研究所_实验物理中心
高能物理研究所_加速器中心
作者单位中国科学院高能物理研究所
推荐引用方式
GB/T 7714
Bakina, O,Baranov, D,Denisenko, I,et al. Deep learning for track recognition in pixel and strip-based particle detectors[J]. JOURNAL OF INSTRUMENTATION,2022,17(12):P12023.
APA Bakina, O.,Baranov, D.,Denisenko, I.,Goncharov, P.,Nechaevskiy, A.,...&Zhemchugov, A.(2022).Deep learning for track recognition in pixel and strip-based particle detectors.JOURNAL OF INSTRUMENTATION,17(12),P12023.
MLA Bakina, O,et al."Deep learning for track recognition in pixel and strip-based particle detectors".JOURNAL OF INSTRUMENTATION 17.12(2022):P12023.

入库方式: OAI收割

来源:高能物理研究所

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