Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
Maximum Classifier Discrepancy for Unsupervised Domain Adaptation 基本問題和動機： 已經有很多工作將對抗學習方法應用到領域自適應當中，這種方法通過訓練域分類器網絡(即判別器)來區分特徵爲源域或者目標域，以及訓練一個特徵生成網絡來模擬判別器。然而，這種域分類器僅僅嘗試去區分特徵爲一個源域還是一個目標域，因此並沒有考慮類別之間的task
相關文章
- 1. Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
- 2. [CVPR 2018]Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
- 3. [論文閱讀筆記@2019.6] Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
- 4. 讀論文《Maximum Classifier Discrepancy for Unsupervised Domain Adaptation》後的總結
- 5. Re-weighted adversarial adaptation network for unsupervised domain adaptation
- 6. Geodesic flow kernel for unsupervised domain adaptation
- 7. [cvpr2017]Deep Hashing Network for Unsupervised Domain Adaptation
- 8. CVPR2019 Transferrable Prototypical Networks for Unsupervised Domain Adaptation
- 9. maximum mean discrepancy
- 10. [cvpr2017]Mind the Class Weight Bias: Weighted Maximum Mean Discrepancy for Unsupervised DA
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相關文章
- 1. Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
- 2. [CVPR 2018]Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
- 3. [論文閱讀筆記@2019.6] Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
- 4. 讀論文《Maximum Classifier Discrepancy for Unsupervised Domain Adaptation》後的總結
- 5. Re-weighted adversarial adaptation network for unsupervised domain adaptation
- 6. Geodesic flow kernel for unsupervised domain adaptation
- 7. [cvpr2017]Deep Hashing Network for Unsupervised Domain Adaptation
- 8. CVPR2019 Transferrable Prototypical Networks for Unsupervised Domain Adaptation
- 9. maximum mean discrepancy
- 10. [cvpr2017]Mind the Class Weight Bias: Weighted Maximum Mean Discrepancy for Unsupervised DA