Self-training with Noisy Student improves ImageNet classification論文解析
一.摘要 首先，本文開門見山給出實驗結果在ImageNet上的提升。之後給出了他的實現方法，總的來說這篇文章結合了（1）知識蒸餾（2）半監督學習（3）模型噪音以及數據噪音 ，想要了解基礎知識的可以先看博客：知識蒸餾(Knowledge Distillation)、半監督學習(semi-supervised learning)以及弱監督學習(weak-supervised learning) 總結作
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相關文章
- 1. Self-training with Noisy Student improves ImageNet classification閱讀筆記
- 2. Self-training with Noisy Student
- 3. 論文ImageNet Classification with Deep Convolutional Neural Networks（Alexnet2012）
- 4. Pre-training on Grayscale ImageNet Improves Medical Image Classification
- 5. ImageNet Classification with Deep Convolutional Neural Networks
- 6. 《ImageNet Classification with Deep Convolutional Neural Network》
- 7. 讀文獻——《ImageNet classification with deep convolutional neural networks》
- 8. ImageNet Classification with Deep Convolutional Neural Networks -- 解讀
- 9. 3.ImageNet Classification with Deep Convolutional Neural Network（AlexNet）論文學習
- 10. 論文筆記：ImageNet Classification with Deep Convolutional Neural Networks