EffNet: An Efficient Structure for Convolutional Neural Networks

时间 2020-12-29

标签 CNN 繁體版

原文原文链接

EffeNet对MoblieNet网络进行改进,主要思想为: 首先,将MoblieNet的 3×3 的depthwise convolution层分解为两个 3×1 , 1×3 depthwise convolution层.这样便可以在第一层之后就采用pool操作,从而减少第二层的计算量. 如图1所示,在第一个卷积层之后,使用 1×2 max pooling操作.在第二个卷积层之后,用 2×1 ,

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1. 【论文解读】EffNet: AN EFFICIENT STRUCTURE FOR CONVOLUTIONAL NEURAL NETWORKS
2. Paper Reading：MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
3. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
4. ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
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6. 论文笔记：An Efficient Hardware Accelerator for Structured Sparse Convolutional Neural Networks on FPGAs
7. 论文笔记：An Efficient Hardware Accelerator for Sparse Convolutional Neural Networks on FPGAs
8. Understanding Convolutional Neural Networks for NLP
9. [转] Understanding Convolutional Neural Networks for NLP
10. Reading Note: MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
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1. 【论文解读】EffNet: AN EFFICIENT STRUCTURE FOR CONVOLUTIONAL NEURAL NETWORKS
2. Paper Reading：MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
3. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
4. ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
5. Pruning Convolutional Neural Networks For Resource Efficient Inference
6. 论文笔记：An Efficient Hardware Accelerator for Structured Sparse Convolutional Neural Networks on FPGAs
7. 论文笔记：An Efficient Hardware Accelerator for Sparse Convolutional Neural Networks on FPGAs
8. Understanding Convolutional Neural Networks for NLP
9. [转] Understanding Convolutional Neural Networks for NLP
10. Reading Note: MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

>>更多相关文章<<