ADDA: Adversarial Discriminative Domain Adaptation
ADDA原理理解 ADDA中源域和目標域經過不同的映射來實現對齊。 ADDA的目標函數包括三項： 1.源域的分類誤差項 2.域分類器的分類誤差項 3.生成器在目標域的誤差項 1.源域的分類誤差項 源域數據在經過映射Ms後的分類誤差最小： 2.域分類器的分類誤差項 在源域和目標域分別經過Ms和Mt的映射後，經過域分類器進行分類，把源域和目標域
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相關文章
- 1. [cvpr2017]Adversarial Discriminative Domain Adaptation
- 2. 【Transfer Learning】Adversarial Discriminative Domain Adaptation
- 3. 2017CVPR--Adversarial Discriminative Domain Adaptation 對抗判別域適應
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- 5. M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning
- 6. Adversarial Discriminative Domain Adaption 閱讀筆記
- 7. 【論文翻譯】DANN的改進ADDA Multimodal Vigilance Estimation with Adversarial Domain Adaptation Networks
- 8. Domain Adaptation 與 Generative Adversarial Network
- 9. Re-weighted adversarial adaptation network for unsupervised domain adaptation
- 10. Importance Weighted Adversarial Nets for Partial Domain Adaptation