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1
Research on Rebar Counting Based on YOLO-Rebar Model:
, In:
2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)
,
Wang, Haijun
;
Long, Minjian
;
Wang, Jianchun
. - p. 356-361 , 2022
Link:
https://doi.org/10.1109/AEMCSE55572.2022.00078
RT T1 <cTitle>2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE)</cTitle>: T1 <Title>Research on Rebar Counting Based on YOLO-Rebar Model</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9948329&Exemplar=1&LAN=DE A1 Wang, Haijun A1 Long, Minjian A1 Wang, Jianchun A1 Guan, Congcong YR 2022 K1 Training K1 Visualization K1 Computational modeling K1 Memory management K1 Graphics processing units K1 Production K1 Object detection K1 Rebar counting K1 YOLOv3 K1 Model evaluation SP 356 OP 361 LK http://dx.doi.org/https://doi.org/10.1109/AEMCSE55572.2022.00078 DO https://doi.org/10.1109/AEMCSE55572.2022.00078 SF ELIB - SuUB Bremen
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