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1
A Deep Learning-Based Methodology for Rapidly Detecting the..:
, In:
2020 IEEE USNC-CNC-URSI North American Radio Science Meeting (Joint with AP-S Symposium)
,
Dai, Qiqi
;
Wen, Bihan
;
Lee, Yee Hui
... - p. 139-140 , 2020
Link:
https://doi.org/10.23919/USNC/URSI49741.2020.9321692
RT T1 <cTitle>2020 IEEE USNC-CNC-URSI North American Radio Science Meeting (Joint with AP-S Symposium)</cTitle>: T1 <Title>A Deep Learning-Based Methodology for Rapidly Detecting the Defects inside Tree Trunks via GPR</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9321692&Exemplar=1&LAN=DE A1 Dai, Qiqi A1 Wen, Bihan A1 Lee, Yee Hui A1 Yucel, Abdulkadir C. A1 Ow, Genevieve A1 Mohd Yusof, Mohamed Lokman YR 2020 K1 Vegetation K1 Trajectory K1 Monitoring K1 Time-domain analysis K1 Ground penetrating radar K1 Finite difference methods K1 Training K1 convolutional neural network (CNN) K1 deep learning K1 defect detection K1 ground-penetrating radar (GPR) K1 tree health monitoring SP 139 OP 140 LK http://dx.doi.org/https://doi.org/10.23919/USNC/URSI49741.2020.9321692 DO https://doi.org/10.23919/USNC/URSI49741.2020.9321692 SF ELIB - SuUB Bremen
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