Mitigate
发表于 2025-3-28 14:44:23
https://doi.org/10.1007/978-3-031-20995-6ations that are more suitable for medical segmentation tasks, (2) self-supervised ImageNet models learn holistic features more effectively than supervised ImageNet models, and (3) continual pre-training can bridge the domain gap between natural and medical images. We hope that this large-scale open
终端
发表于 2025-3-28 22:28:40
http://reply.papertrans.cn/29/2825/282483/282483_42.png
沙文主义
发表于 2025-3-29 01:07:10
http://reply.papertrans.cn/29/2825/282483/282483_43.png
结果
发表于 2025-3-29 05:31:20
http://reply.papertrans.cn/29/2825/282483/282483_44.png
不足的东西
发表于 2025-3-29 08:32:11
https://doi.org/10.1007/978-3-031-23629-7 test instance until it satisfies the learned shape prior. Our method is simple to implement and increases model performance. Moreover, it opens new directions for re-using mask discriminators at inference. We release the code used for the experiments at ..
不规则
发表于 2025-3-29 11:41:49
http://reply.papertrans.cn/29/2825/282483/282483_46.png
unstable-angina
发表于 2025-3-29 17:39:15
https://doi.org/10.1007/978-3-031-23759-1o extract systematically better representations for the target domain. In particular, we address the challenge of enhancing performance on VERDICT-MRI, an advanced diffusion-weighted imaging technique, by exploiting labeled mp-MRI data. When compared to several unsupervised domain adaptation approac
Ceremony
发表于 2025-3-29 21:23:37
http://reply.papertrans.cn/29/2825/282483/282483_48.png
JAMB
发表于 2025-3-29 23:52:40
http://reply.papertrans.cn/29/2825/282483/282483_49.png
PATHY
发表于 2025-3-30 05:59:26
http://reply.papertrans.cn/29/2825/282483/282483_50.png