DropBlock: A regularization method for convolutional networks論文解讀
Paper：https://arxiv.org/pdf/1810.12890.pdf Code：https://github.com/miguelvr/dropblock & https://github.com/DHZS/tf-dropblock 摘要：當前深度神經網絡被過度參數化或者訓練集多樣性充足或合適的正則化（權重衰減、丟棄法）訓練時，通常會取得很好地效果。儘管dropout被廣泛地用作全
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相關文章
- 1. DropBlock： A regularization method for convolutional networks
- 2. 《DropBlock: A regularization method for convolutional networks》筆記
- 3. （原）DropBlock A regularization method for convolutional networks
- 4. 論文解讀：Graph Convolutional Networks for Text Classifification
- 5. Fully Convolutional Networks for Semantic Segmentation 論文解讀
- 6. 論文閱讀-Fast Algorithms for Convolutional Neural Networks
- 7. 論文閱讀：《Convolutional Neural Networks for Sentence Classification》
- 8. 《Convolutional Neural Networks for Sentence Classification》論文研讀
- 9. 《Fully Convolutional Networks for Semantic Segmentation》論文閱讀
- 10. 論文閱讀：Fully Convolutional Networks for Semantic Segmentation