EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks (2019)論文筆記
論文連接: EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. 代碼連接: tensorflow.html 摘要 簡介 傳統Scaling up的方法 Compound Scaling方法 簡介 加深擴大神經網絡(model scaling up)能夠有效提高模型的準確率，可是計算資源是有限的。本文討論
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- 1. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks（2019）
- 2. #Paper Reading# EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 3. [ICML19]EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
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- 8. [論文解讀]ICML 2019|EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
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相關文章
- 1. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks（2019）
- 2. #Paper Reading# EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 3. [ICML19]EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 4. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 5. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 論文筆記
- 6. 論文筆記：EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 7. Efficientnet: Rethinking model scaling for convolutional neural networks（論文筆記）
- 8. [論文解讀]ICML 2019|EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 9. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks-文獻閱讀筆記
- 10. 論文閱讀：EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks