論文筆記 ——《Unsupervised Domain Adaptation by Backpropagation》
論文筆記 —— 《基於反向傳播的無監督域適應》（《Unsupervised Domain Adaptation by Backpropagation》） 思想 本文側重於將領域適應和深度特徵學習結合在一個訓練過程中(深度領域適應)。我們的目標是將領域自適應嵌入到學習表示的過程中，使最終的分類決策基於對領域變化既具有區別性又不變性的特徵，即在源域和目標域中具有相同或非常相似的分佈。 這樣，得到的前饋
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相關文章
- 1. 論文筆記：Unsupervised Domain Adaptation by Backpropagation
- 2. Unsupervised Domain Adaptation by Backpropagation(2015)學習筆記
- 3. Unsupervised Domain Adaptation by Backpropagation(2015)
- 4. DANN：Unsupervised Domain Adaptation by Backpropagation
- 5. Unsupervised Domain Adaptation by Backpropagation(2015)學習總結
- 6. 筆記： Gradient Reversal Layer (unsupervised domain adaptation by backpropagation. ICML 2015)
- 7. unsupervised image segmentation by backpropagation-論文筆記
- 8. [論文閱讀筆記@2019.6] Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
- 9. 《Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision》論文筆記
- 10. 《A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification》論文筆記