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Research and application of Faster RCNN-based video action ..:
, In:
2023 Asia Conference on Power, Energy Engineering and Computer Technology (PEECT)
,
Fu, Da
;
Liang, Hao
;
Wang, Fangzhou
. - p. 89-93 , 2023
Link:
https://doi.org/10.1109/PEECT59566.2023.00023
RT T1 <cTitle>2023 Asia Conference on Power, Energy Engineering and Computer Technology (PEECT)</cTitle>: T1 <Title>Research and application of Faster RCNN-based video action detection model</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10483516&Exemplar=1&LAN=DE A1 Fu, Da A1 Liang, Hao A1 Wang, Fangzhou A1 Zhang, Chaoli YR 2023 K1 Deep learning K1 Computational modeling K1 Pipelines K1 Safety management K1 Production K1 Feature extraction K1 Power industry K1 faster r-cnn K1 dual channel theory K1 deep learning K1 apparent features K1 action features K1 time-space domain feature K1 action pipeline model SP 89 OP 93 LK http://dx.doi.org/https://doi.org/10.1109/PEECT59566.2023.00023 DO https://doi.org/10.1109/PEECT59566.2023.00023 SF ELIB - SuUB Bremen
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