EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Abstract: CNN通常都是在固定资源预算下开发设计，如果有更多的可用资源再将模型结构放大以获取更高的精度。这篇文章系统性的研究了模型的缩放并且仔细验证了网络深度，宽度，分辨率之间的平衡可以使网络获得更好地性能表现。基于此发现，提出了一个新的网络缩放方法----利用一个简单且高效的复合系数来完成对深度/宽度/分辨率所有维度的统一缩放。文中通过MobileNets和ResNets对这种方法的高
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- 1. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks（2019）
- 2. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 3. [ICML19]EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 4. #Paper Reading# 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. 论文阅读：EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 8. [论文解读]ICML 2019|EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 9. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks (2019)论文笔记
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相关文章
- 1. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks（2019）
- 2. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 3. [ICML19]EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 4. #Paper Reading# 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. 论文阅读：EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 8. [论文解读]ICML 2019|EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- 9. EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks (2019)论文笔记
- 10. 【论文解读】EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks