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1 Ergebnisse
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Minimizing the Number of Views in Few-View Computed Tomogra..:
, In:
2022 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)
,
Vlasov, V. V.
;
Konovalov, A. B.
- p. 1063-1067 , 2022
Link:
https://doi.org/10.1109/ICIEAM54945.2022.9787247
RT T1
2022 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)
: T1
Minimizing the Number of Views in Few-View Computed Tomography: a Deep Learning Approach
UL https://suche.suub.uni-bremen.de/peid=ieee-9787247&Exemplar=1&LAN=DE A1 Vlasov, V. V. A1 Konovalov, A. B. YR 2022 K1 Deep learning K1 Pipelines K1 Phantoms K1 Inspection K1 Industrial engineering K1 Minimization K1 Numerical models K1 few-view computed tomography K1 ART-TVS K1 deep learning (DL) K1 DL-segmentation K1 deep convolutional neural network (DCNN) K1 U-Net K1 ART-TVS-DL SP 1063 OP 1067 LK http://dx.doi.org/https://doi.org/10.1109/ICIEAM54945.2022.9787247 DO https://doi.org/10.1109/ICIEAM54945.2022.9787247 SF ELIB - SuUB Bremen
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