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很好的一篇论文!但是如果我选择从头开始训练这个网络,那么这些local,part模块的裁剪还能train的成功吗?就是不使用预训练,对实验结果的影响有多大的影响呢?期待您的回复!
The text was updated successfully, but these errors were encountered:
谢谢! 通常都会使用基于imagenet预训练的权重,可以得到更好的性能。 对于论文中的方法,如果不使用预训练权重的话,local,part模块在训练前期提出的结果将产生副作用,至于后期能否收敛没有验证过。 不过可以先使用原图只训练第一个分支,待网络具有一定的拟合能力后再加入后续两个分支到训练的过程中,应该能实现比原图只训练第一个分支更好的性能,具体好多少这个没有试验验证过。
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感谢您的回复!
感觉本篇论文论文精度的提升全靠预训练权重。。。
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很好的一篇论文!但是如果我选择从头开始训练这个网络,那么这些local,part模块的裁剪还能train的成功吗?就是不使用预训练,对实验结果的影响有多大的影响呢?期待您的回复!
The text was updated successfully, but these errors were encountered: