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1 Ergebnisse
1
A Weakly-Supervised Anomaly Detection Method via Adversaria..:
, In:
2022 IEEE International Conference on Consumer Electronics (ICCE)
,
Li, He
;
Iwamoto, Yutaro
;
Han, Xianhua
... - p. 1-4 , 2022
Link:
https://doi.org/10.1109/ICCE53296.2022.9730129
RT T1 <cTitle>2022 IEEE International Conference on Consumer Electronics (ICCE)</cTitle>: T1 <Title>A Weakly-Supervised Anomaly Detection Method via Adversarial Training for Medical Images</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9730129&Exemplar=1&LAN=DE A1 Li, He A1 Iwamoto, Yutaro A1 Han, Xianhua A1 Lin, Lanfen A1 Tong, Ruofeng A1 Hu, Hongjie A1 Furukawa, Akira A1 Kanasaki, Shuzo A1 Chen, Yen-Wei YR 2022 SN 2158-4001 K1 Learning systems K1 Training K1 Measurement uncertainty K1 Liver K1 Generators K1 Indexes K1 Image reconstruction K1 anomaly detection K1 weakly-supervised learning K1 generative adversarial networks K1 medical images SP 1 OP 4 LK http://dx.doi.org/https://doi.org/10.1109/ICCE53296.2022.9730129 DO https://doi.org/10.1109/ICCE53296.2022.9730129 SF ELIB - SuUB Bremen
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