#Paper Reading# EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
論文題目: EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 論文地址: https://arxiv.org/abs/1905.11946 論文發表於: ICML 2019 論文大體內容： 本文主要提出了EfficientNet模型，來同時考慮網絡的deep、width、resolution（分辨率）三
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- 4. 論文閱讀：EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
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- 6. (DL Classification)Review: EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 7. [論文解讀]ICML 2019|EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 8. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks (2019)論文筆記
- 9. 【論文解讀】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
- 2. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks（2019）
- 3. [ICML19]EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 4. 論文閱讀：EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 5. EfficientNet 《EfficientNet:Rethinking model scaling for convolutional neural networks》
- 6. (DL Classification)Review: EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 7. [論文解讀]ICML 2019|EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 8. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks (2019)論文筆記
- 9. 【論文解讀】EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 10. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks 論文筆記