Comments (5)
您好,大神,使用您提供的ProxylessBackbone作为骨架网络,然后接入rnn编码,利用ctc loss训练,效果基本得不到提升,想问一下怎么回事呢?您的这个NAS搜索得到网络和vgg还没有vgg网络精度高,想问一下大佬是什么原因呢 @quanmingyao @huizhang0110
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您好,我也在学习这个project,能否加您的联系方式讨论。([email protected])
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您好,@wuxiaolianggit
NAS的优点是针对任务和要求去定制结构。我们在特定的数据集和识别pipeline下找到的backbone,并不一定能直接适用您的数据和模型结构上面,相比于人类专家手工设计的结构,其泛化性确实存在问题。
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好的,了解了,多谢大神回复 @huizhang0110
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@ZhangQihan 可以啊,可以以多交流一下
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Related Issues (9)
- Use the Compact Structure for recognition HOT 3
- Download of pretrained model from baidu HOT 1
- UserWarning: RNN module weights are not part of single contiguous chunk of memory HOT 2
- Muti-gpu search/retrain support ? HOT 2
- 关于模型使用的一些疑问 HOT 6
- Network always choise big kernel size and expansion factor t always is 6
- 文件缺失
- loss
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