How transferable are features in deep nerual networks? 【paper review】
遷移學習是什麼： 遷移學習就是用已經學過的知識【源域，source data】來進行新知識的學習【目標域，target data】，也就是說舉一反三，用一個已經訓練好的模型，去訓練一個新的模型。 論文地址:點擊打開鏈接 【有了這個基本的認知後，我們來看下這篇論文】： 在很多訓練好的DNN模型中，前幾層是作用於通用特徵的識別，比如識別一個圖片裏面有沒有一條線，而不是特有特徵的識別。所以前幾層可以使
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相關文章
- 1. How transferable are features in deep neural networks?
- 2. How transferable are features in deep neural networks? 論文筆記
- 3. 論文筆記：How transferable are features in deep neural networks?
- 4. Learning Transferable Features with Deep Adaptation Networks
- 5. 翻譯「Learning Transferable Features with Deep Adaptation Networks」
- 6. How to review a paper
- 7. 對於DAN方法的解讀-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