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使用ghostconv代替bottelneck里面的普通conv,进行实例分割训练的损失和精度都没有之前的好,难道是还有其他的地方要改进吗?不过参数量和运算量有降低,
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正常吧,看精度损失多少
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白色的是在bottleneck里面用ghost卷积的,黑色是普通卷积,结果都是截取的300轮里面最好的,麻烦看一下是否正常呢。
看起来正常。把原模型通道数减少,参数量和用ghost卷积的差不多程度,看看谁精度高
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使用ghostconv代替bottelneck里面的普通conv,进行实例分割训练的损失和精度都没有之前的好,难道是还有其他的地方要改进吗?不过参数量和运算量有降低,
The text was updated successfully, but these errors were encountered: