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WingsNet中注意力模块的疑惑 #11
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3D的中间结果太占显存了,所以原始分辨率的层就用简单的,下采样后可以用更复杂的。
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发送时间: 星期五, 2023年 2 月 10日 上午 11:37:37
主题: [haozheng-sjtu/3d-airway-segmentation] WingsNet中注意力模块的疑惑 (Issue #11)
作者您好,首先感谢公开支气管分割框架,对于我的帮助很大!看了您的《Alleviating Class-wise Gradient Imbalance for
Pulmonary Airway Segmentation》后,在网络设计方面有一些疑惑,您参考的论文将SE拓展为cSE(原始的), sSE(WingsNet采用的)和scSE(二者结合)的,参考的论文中做过一些对照实验,结果表明第三类变种在医学分割任务中性能最好,您在WingsNet中为什么采用sSE而不是scSE呢?
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确实,谢谢
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主题: Re: [haozheng-sjtu/3d-airway-segmentation] WingsNet中注意力模块的疑惑 (Issue #11)
3D的中间结果太占显存了,所以原始分辨率的层就用简单的,下采样后可以用更复杂的。
发件人: "Itsanewday" ***@***.***>
收件人: "haozheng-sjtu/3d-airway-segmentation" ***@***.***>
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发送时间: 星期五, 2023年 2 月 10日 上午 11:37:37
主题: [haozheng-sjtu/3d-airway-segmentation] WingsNet中注意力模块的疑惑 (Issue #11)
作者您好,首先感谢公开支气管分割框架,对于我的帮助很大!看了您的《Alleviating Class-wise Gradient Imbalance for
Pulmonary Airway Segmentation》后,在网络设计方面有一些疑惑,您参考的论文将SE拓展为cSE(原始的), sSE(WingsNet采用的)和scSE(二者结合)的,参考的论文中做过一些对照实验,结果表明第三类变种在医学分割任务中性能最好,您在WingsNet中为什么采用sSE而不是scSE呢?
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Reply to this email directly, [ #11 | view it on GitHub ] , or [ https://github.com/notifications/unsubscribe-auth/ATQRWJLHBD4LOAWEJJCDYSTWWWZYDANCNFSM6AAAAAAUXKGXNA | unsubscribe ] .
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作者您好,首先感谢公开支气管分割框架,对我帮助很大!看了您的《Alleviating Class-wise Gradient Imbalance for
![image](https://user-images.githubusercontent.com/21170245/217994832-e9244080-5c17-448f-a026-d62de32bee0a.png)
Pulmonary Airway Segmentation》后,在网络设计方面有一些疑惑: 您参考的论文将SE拓展为cSE(原始的), sSE(WingsNet采用的)和scSE(二者结合),参考的论文中做过一些对照实验,结果表明第三类变种在医学分割任务中性能最好,
您在WingsNet中为什么采用sSE而不是scSE呢?
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