論文閱讀筆記《Baby Steps Towards Few-Shot Learning with Multiple Semantics》
核心思想 本文提出一種結合多種語義信息的小樣本學習算法。首先作者提到人類的幼兒在學習新的事物時，通常是利用多種語義信息綜合學習的，比如你給他看一隻狗，他不僅接收到視覺和簡單的語義標籤信息，你還會給他描述這隻狗有金色的毛髮，它還會汪汪叫。如此一來幼兒就可接收到多種語義信息，幫助他學習識別狗。正是出於這種思想，作者提出利用多種更爲豐富的語義信息來幫助模型實現小樣本學習，網絡的結構如下圖所示。
相關文章
- 1. 論文：Baby Steps Towards Few-Shot Learning with Multiple Semantics
- 2. Machine Learning & Deep Learning 論文閱讀筆記
- 3. 論文閱讀筆記：FULLY CONVOLUTIONAL MULTI-CLASS MULTIPLE INSTANCE LEARNING
- 4. SRN: Towards Accurate Scene Text Recognition with Semantic Reasoning Networks ---論文閱讀筆記
- 5. Sentiment Classification towards Question-Answering with Hierarchical Matching Network 論文閱讀筆記
- 6. 【論文閱讀筆記】Deep Neural Network Compression with Single and Multiple Level Quantization
- 7. [論文閱讀]Learning Discriminative Features with Multiple Granularityfor Person Re-Identification
- 8. Deep Mutual Learning論文閱讀筆記
- 9. 論文閱讀筆記（四十）：Learning Spatiotemporal Features with 3D Convolutional Networks（C3D）
- 10. 論文閱讀筆記《Active One-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：Baby Steps Towards Few-Shot Learning with Multiple Semantics
- 2. Machine Learning & Deep Learning 論文閱讀筆記
- 3. 論文閱讀筆記：FULLY CONVOLUTIONAL MULTI-CLASS MULTIPLE INSTANCE LEARNING
- 4. SRN: Towards Accurate Scene Text Recognition with Semantic Reasoning Networks ---論文閱讀筆記
- 5. Sentiment Classification towards Question-Answering with Hierarchical Matching Network 論文閱讀筆記
- 6. 【論文閱讀筆記】Deep Neural Network Compression with Single and Multiple Level Quantization
- 7. [論文閱讀]Learning Discriminative Features with Multiple Granularityfor Person Re-Identification
- 8. Deep Mutual Learning論文閱讀筆記
- 9. 論文閱讀筆記（四十）：Learning Spatiotemporal Features with 3D Convolutional Networks（C3D）
- 10. 論文閱讀筆記《Active One-shot Learning》