論文水記|How to Train Triplet Networks with 100K Identities?
這是來自獵戶星空的關於人臉識別的文章 作者 Chong Wang ；Xue Zhang ；Xipeng Lan https://arxiv.org/abs/1709.02940 好久沒有寫博客了，水一篇。。。 一句話總結 對應triplet的訓練，多采用OHNM的方式挖掘困難負樣本，然而隨着訓練數據的增加，easy-triplet更多，困難樣本的搜索空間增大，於是本文將訓練數據分爲若干小部分，每部
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相關文章
- 1. How to Train Triplet Networks with 100K Identities?論文簡略翻譯
- 2. (zhuan) How to Train Neural Networks With Backpropagation
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- 4. How to train Custom Dataset
- 5. 【筆記】Loc2Vec: Learning location embeddings with triplet-loss networks
- 6. 論文閱讀筆記：From Image-level to Pixel-level Labeling with Convolutional Networks
- 7. Back to Simplicity How to Train Accurate BNNs from Scratch
- 8. 1606.End--to-End Comparative Attention Networks for Person Re-identification 論文筆記
- 9. How to Train a Final Machine Learning Model
- 10. 《Image-to-Image Translation with Conditional Adversarial Networks》論文筆記