Dynamic Few-Shot Visual Learning without Forgetting||论文阅读
文章介绍： 这篇文章和前面两篇的基本思想也非常类似，也是直接用已有的大的数据集训练，核心还是在于如何处理新task 新class的输出。 那么这篇文章的idea和上一篇其实没有本质的区别，或者说几乎就是一样的，先用training set训练出一个feature extractor，然后对于新的few shot training data，通过一个few-shot classification w
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相关文章
- 1. 论文阅读笔记《Dynamic Few-Shot Visual Learning without Forgetting》
- 2. Dynamic Few-Shot Visual Learning without Forgetting
- 3. Incremental Learning of Object Detectors without Catastrophic Forgetting 论文阅读
- 4. Learning without Forgetting 翻译
- 5. Machine Learning & Deep Learning 论文阅读笔记
- 6. 论文阅读笔记《One-Shot Visual Imitation Learning via Meta-Learning》
- 7. Incremental Learning of Object Detectors without Catastrophic Forgetting详解
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- 9. 论文阅读 (十九)：Deep Multi-instance Learning with Dynamic Pooling (2018DP-MINN)
- 10. 论文阅读笔记之——《Dynamic Conditional Networks for Few-Shot Learning》