Unsupervised Feature Learning via Non-Parametric Instance Discrimination
論文地址：Unsupervised Feature Learning via Non-Parametric Instance Discrimination github代碼:NCE代碼 摘要: 在有標籤數據上訓練的神經網絡分類器能夠很好的捕捉圖片間的視覺相似性。文章假設：我們能通過訓練基於實例（將每一個樣本視爲單獨的類別）的分類器代替基於類別的分類器，得到可以捕捉視覺相似性的特徵表達。我們將其總結
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相關文章
- 1. [解讀] Unsupervised Feature Learning via Non-Parametric Instance Discrimination
- 2. Unsupervised Feature Learning via Non-parametric Instance Discrimination
- 3. 論文閱讀筆記：Unsupervised Feature Learning via Non-Parametric Instance Discrimination
- 4. Effective Feature Learning with Unsupervised Learning in MOOCs
- 5. Query-Oriented Multi-Document Summarization via Unsupervised Deep Learning
- 6. 論文閱讀:Unsupervised Deep Learning by Neighbourhood Discovery
- 7. 《論文閱讀》Unsupervised Person Re-identification via Softened Similarity Learning
- 8. AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks
- 9. 【小白筆記】Correlation Tracking via Joint Discrimination and Reliability Learning
- 10. Supervised learning and Unsupervised learning