論文筆記：Prototypical Networks for Few-shot Learning
Prototypical Networks for Few-shot Learning（用於小樣本學習的原型網絡） 論文中心思想：通過神經網絡學會一個「好的」映射，將各個樣本投影到同一空間中，對於每種類型的樣本提取他們的中心點(mean)作爲原型（prototype）。使用歐幾里得距離作爲距離度量，訓練使得測試樣本到自己類別原型的距離越近越好，到其他類別原型的距離越遠越好。測試時，通過對到每類原型
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相關文章
- 1. 論文閱讀 Prototypical Networks for Few-shot Learning
- 2. prototypical networks for few-shot learning論文
- 3. 論文閱讀筆記 Prototypical Networks for Few-shot Learning
- 4. 原型網絡2017：《Prototypical Networks for Few-shot Learning》論文筆記
- 5. Prototypical Networks for Few-shot Learning
- 6. 論文筆記：Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification
- 7. Learning Convolutional Neural Networks for Graphs論文筆記
- 8. Learning Deconvolution Network for Segmentic segmentation_ICCV_2015論文筆記
- 9. 論文閱讀筆記《Variational Prototyping-Encoder: One-Shot Learning with Prototypical Images》
- 10. Variational Prototyping-Encoder: One-Shot Learning with Prototypical Images 論文筆記