Dynamic Few-Shot Visual Learning without Forgetting||論文閱讀
文章介紹： 這篇文章和前面兩篇的基本思想也非常類似，也是直接用已有的大的數據集訓練，核心還是在於如何處理新task 新class的輸出。 那麼這篇文章的idea和上一篇其實沒有本質的區別，或者說幾乎就是一樣的，先用training set訓練出一個feature extractor，然後對於新的few shot training data，通過一個few-shot classification w
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相關文章
- 1. 論文閱讀筆記《Dynamic Few-Shot Visual Learning without Forgetting》
- 2. Dynamic Few-Shot Visual Learning without Forgetting
- 3. Incremental Learning of Object Detectors without Catastrophic Forgetting 論文閱讀
- 4. Learning without Forgetting 翻譯
- 5. Machine Learning & Deep Learning 論文閱讀筆記
- 6. 論文閱讀筆記《One-Shot Visual Imitation Learning via Meta-Learning》
- 7. Incremental Learning of Object Detectors without Catastrophic Forgetting詳解
- 8. 論文閱讀：Dual Supervised Learning
- 9. 論文閱讀 (十九)：Deep Multi-instance Learning with Dynamic Pooling (2018DP-MINN)
- 10. 論文閱讀筆記之——《Dynamic Conditional Networks for Few-Shot Learning》