论文阅读笔记《Finding Task-Relevant Features for Few-Shot Learning by Category Traversal 》
核心思想 本文在度量学习算法的基础上提出了一种特征学习模块，用于改进原有算法特征提取网络的表征能力，进而提高小样本分类的准确性。本文设计的种类遍历模块（Category Traversal Module，CTM）可以作为一种即插即用的模块，直接添加到原有算法的网络中。相对于原有的特征提取网络，CTM有针对性地提取了“类内共有特征（intra-class commonality）”和“类间独有特
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相关文章
- 1. Finding Task-Relevant Features for Few-Shot Learning by Category Traversal 论文笔记
- 2. Finding Task-Relevant Features for Few-Shot Learning by Category Traversal论文笔记
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