Ranked List Loss for Deep Metric Learning
CVPR2019 度量學習 Ranked List Loss for Deep Metric Learningweb 原文連接：https://arxiv.org/abs/1903.03238算法 度量學習在圖像識別、檢索等領域有着普遍應用。本文提出了一種新的方法，Ranked List Loss(RLL)。利用該損失函數能夠小幅提高網絡的準確性。話很少說，直接上圖。 上圖是幾種常見的損失函數，最
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相關文章
- 1. Ranked List Loss for Deep Metric Learning
- 2. 【2017_ICCV】Deep Metric Learning with Angular Loss
- 3. Deep Reinforcement Learning for List-wise Recommendations
- 4. deep learning loss總結
- 5. Deep Metric Learning with Hierarchical Triplet Loss 閱讀筆記
- 6. M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning
- 7. 論文筆記《Deep Cosine Metric Learning for Person Re-Identification》
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- 9. Margin Sample Mining Loss: A Deep Learning Based Method for Person Re-identification
- 10. 度量學習 度量函數 metric learning deep metric learning 深度度量學習