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Research on Methods of Improving Robustness of Deep Learnin..:
, In:
2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA)
,
Xiao, Juan
;
Long, Haojian
;
Li, Renfa
. - p. 644-647 , 2022
Link:
https://doi.org/10.1109/AEECA55500.2022.9919014
RT T1 <cTitle>2022 IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA)</cTitle>: T1 <Title>Research on Methods of Improving Robustness of Deep Learning Algorithms in Autonomous Driving</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9919014&Exemplar=1&LAN=DE A1 Xiao, Juan A1 Long, Haojian A1 Li, Renfa A1 Li, Faying YR 2022 K1 Training K1 Degradation K1 Computer network reliability K1 Computational modeling K1 Object detection K1 Benchmark testing K1 Reliability engineering K1 autonomous driving K1 image damage K1 stylize K1 robustness SP 644 OP 647 LK http://dx.doi.org/https://doi.org/10.1109/AEECA55500.2022.9919014 DO https://doi.org/10.1109/AEECA55500.2022.9919014 SF ELIB - SuUB Bremen
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