論文閱讀筆記《Few-Shot Learning with Global Class Representations》
小樣本學習&元學習經典論文整理||持續更新 核心思想 本文提出一種基於度量學習的小樣本學習算法。與其他算法將訓練集分成基礎類別和新類別，進行兩個階段的訓練方式不同，本文將包含大量樣本的基礎類別和包含少量樣本的新類別合在一起進行訓練，得到每個類別的表徵（原型）稱之爲全局類別表徵（Global Class Representations，GCR）。然後對於每個Episode中的支持集樣本得到對應的
相關文章
- 1. [論文筆記] Few-Shot Learning with Global Class Representations
- 2. Machine Learning & Deep Learning 論文閱讀筆記
- 3. Few-Shot Learning with Global Class Representations筆記整理
- 4. 論文閱讀筆記《Large-Scale Few-Shot Learning: Knowledge Transfer With Class Hierarchy》
- 5. 論文閱讀：DeepWalk Online Learning of Social Representations
- 6. 1604. Learning deep feature representations with domain guided dropout for re-id論文閱讀筆記
- 7. 論文閱讀筆記《Learning Compositional Representations for Few-Shot Recognition》
- 8. Deep Mutual Learning論文閱讀筆記
- 9. 論文閱讀筆記：FULLY CONVOLUTIONAL MULTI-CLASS MULTIPLE INSTANCE LEARNING
- 10. 論文閱讀筆記《CANet: Class-Agnostic Segmentation Networks withAttentive Few-Shot Learning》
- 更多相關文章...
- • RSS 閱讀器 - RSS 教程
- • C# 文本文件的讀寫 - C#教程
- • Tomcat學習筆記（史上最全tomcat學習筆記）
- • JDK13 GA發佈：5大特性解讀
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. [論文筆記] Few-Shot Learning with Global Class Representations
- 2. Machine Learning & Deep Learning 論文閱讀筆記
- 3. Few-Shot Learning with Global Class Representations筆記整理
- 4. 論文閱讀筆記《Large-Scale Few-Shot Learning: Knowledge Transfer With Class Hierarchy》
- 5. 論文閱讀：DeepWalk Online Learning of Social Representations
- 6. 1604. Learning deep feature representations with domain guided dropout for re-id論文閱讀筆記
- 7. 論文閱讀筆記《Learning Compositional Representations for Few-Shot Recognition》
- 8. Deep Mutual Learning論文閱讀筆記
- 9. 論文閱讀筆記：FULLY CONVOLUTIONAL MULTI-CLASS MULTIPLE INSTANCE LEARNING
- 10. 論文閱讀筆記《CANet: Class-Agnostic Segmentation Networks withAttentive Few-Shot Learning》