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1 Ergebnisse
1
Deep Prototypical-Parts Ease Morphological Kidney Stone Ide..:
, In:
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
,
Flores-Araiza, Daniel
;
Lopez-Tiro, Francisco
;
El-Beze, Jonathan
... - p. 295-304 , 2023
Link:
https://doi.org/10.1109/CVPRW59228.2023.00035
RT T1 <cTitle>2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)</cTitle>: T1 <Title>Deep Prototypical-Parts Ease Morphological Kidney Stone Identification and are Competitively Robust to Photometric Perturbations</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10208481&Exemplar=1&LAN=DE A1 Flores-Araiza, Daniel A1 Lopez-Tiro, Francisco A1 El-Beze, Jonathan A1 Hubert, Jacques A1 Gonzalez-Mendoza, Miguel A1 Ochoa-Ruiz, Gilberto A1 Daul, Christian YR 2023 SN 2160-7516 K1 Training K1 Deep learning K1 Visualization K1 Sensitivity K1 Computational modeling K1 Perturbation methods K1 Pattern recognition SP 295 OP 304 LK http://dx.doi.org/https://doi.org/10.1109/CVPRW59228.2023.00035 DO https://doi.org/10.1109/CVPRW59228.2023.00035 SF ELIB - SuUB Bremen
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