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DFANet: Dense Feature Augmentation Network for Printed Circ..:
, In:
2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI)
,
Qin, Jie
;
Zou, Jiayu
;
Li, Donghui
. - p. 513-520 , 2022
Link:
https://doi.org/10.1109/PRAI55851.2022.9904147
RT T1 <cTitle>2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI)</cTitle>: T1 <Title>DFANet: Dense Feature Augmentation Network for Printed Circuit Board Segmentation</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9904147&Exemplar=1&LAN=DE A1 Qin, Jie A1 Zou, Jiayu A1 Li, Donghui A1 Wang, Xingang YR 2022 K1 Training K1 Location awareness K1 Visualization K1 Fuses K1 Printed circuits K1 Transformers K1 Integrated circuit modeling K1 automated signal testing K1 small objects segmentation K1 printed circuit board K1 convolution K1 multi-scale feature K1 cross-attention K1 transformer SP 513 OP 520 LK http://dx.doi.org/https://doi.org/10.1109/PRAI55851.2022.9904147 DO https://doi.org/10.1109/PRAI55851.2022.9904147 SF ELIB - SuUB Bremen
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