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Learning Erosional Probability Maps for Nuclei Instance Seg..:
, In:
2020 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)
,
Huang, Zhongyi
;
Ding, Yao
;
Geng, Ruizhe
... - p. 297-302 , 2020
Link:
https://doi.org/10.1109/MIPR49039.2020.00068
RT T1 <cTitle>2020 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)</cTitle>: T1 <Title>Learning Erosional Probability Maps for Nuclei Instance Segmentation</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9175505&Exemplar=1&LAN=DE A1 Huang, Zhongyi A1 Ding, Yao A1 Geng, Ruizhe A1 He, Hongliang A1 Huang, Xiansong A1 Chen, Jie YR 2020 K1 Image segmentation K1 Training K1 Biomedical imaging K1 Predictive models K1 Testing K1 Detectors K1 Feature extraction K1 nuclei instance segmentation, erosional probability map, deep learning, cell boundary ambiguity SP 297 OP 302 LK http://dx.doi.org/https://doi.org/10.1109/MIPR49039.2020.00068 DO https://doi.org/10.1109/MIPR49039.2020.00068 SF ELIB - SuUB Bremen
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