【論文筆記】Representation Learning by Learning to Count
1、INTRO 這篇文章作者提出一種方法，去計數圖像中的visual primitives從而學習圖像的representation。 2、Transforming Images to Transform Features 作者提出兩點：1）計算視覺原語（visual primitives）的特徵不應受到縮放、二維平移和二維旋轉變換的影響；2）一半的圖像的視覺原語數量應該是小於整幅圖像的。 由此該
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相關文章
- 1. 論文筆記: Inductive Representation Learning on Large Graphs
- 2. 論文筆記：Representation Learning with Contrastive Predictive Coding
- 3. Inductive Representation Learning on Large Graphs論文筆記
- 4. 論文筆記：Inductive Representation Learning on Large Graphs
- 5. [論文筆記]Unsupervised Visual Representation Learning by Context Prediction
- 6. [論文筆記 ECCV2020] Learning to Count in the Crowd from Limited Labeled Data
- 7. Machine Learning & Deep Learning 論文閱讀筆記
- 8. Predictive learning vs. representation learning
- 9. [論文筆記]：GraphSAGE：Inductive Representation Learning on Large Graphs 論文詳解 NIPS 2017
- 10. Convolutional Sequence to Sequence Learning 論文筆記