論文筆記 | A Discriminative Feature Learning Approach for Deep Face Recognition
出處：ECCV 2016 論文：https://kpzhang93.github.io/papers/eccv2016.pdf 代碼：https://github.com/ydwen/caffe-face 摘要： 在大多數可用的CNN中，softmax損失函數被用作訓練深度模型的監督信號。爲了提高深度學習特徵的判別力，本文提出了一種新的監督信號，稱爲center loss。中心損失同時學習每個類別
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相關文章
- 1. A Discriminative Feature Learning Approach for Deep Face Recognition
- 2. A Discriminative Feature Learning Approach for Deep Face Recognition 論文筆記
- 3. 《A Discriminative Feature Learning Approach for Deep Face Recognition》論文筆記
- 4. Center Loss: A Discriminative Feature Learning Approach for Deep Face Recognition（論文閱讀筆記）
- 5. 文獻閱讀 - A Discriminative Feature Learning Approach for Deep Face Recognition
- 6. 閱讀A Discriminative Feature Learning Approach for Deep Face Recognition
- 7. 【人臉識別】A Discriminative Feature Learning Approach for Deep Face Recognition
- 8. 論文筆記（一）Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach
- 9. centerloss系列文章筆記——人臉識別：A Discriminative Feature Learning Approach forDeep Face Recognition
- 10. 論文閱讀理解 - CenterLoss: A Discriminative Feature Learning Approach