How transferable are features in deep nerual networks? 【paper review】

时间 2020-12-24

标签 paper review 繁體版

原文原文链接

迁移学习是什么：迁移学习就是用已经学过的知识【源域，source data】来进行新知识的学习【目标域，target data】，也就是说举一反三，用一个已经训练好的模型，去训练一个新的模型。论文地址:点击打开链接【有了这个基本的认知后，我们来看下这篇论文】：在很多训练好的DNN模型中，前几层是作用于通用特征的识别，比如识别一个图片里面有没有一条线，而不是特有特征的识别。所以前几层可以使

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1. How transferable are features in deep neural networks?
2. How transferable are features in deep neural networks? 论文笔记
3. 论文笔记：How transferable are features in deep neural networks?
4. Learning Transferable Features with Deep Adaptation Networks
5. 翻译“Learning Transferable Features with Deep Adaptation Networks”
6. How to review a paper
7. 对于DAN方法的解读-Learning Transferable Features with Deep Adaptation Networks
8. How to Review a Technical Paper
9. paper review : Deep Audio-Visual learning: A Survey
10. Activation function in Nerual Networks

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