论文笔记-IGCV3：Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks
介绍 在这篇论文中，做者同时使用低秩核和稀疏核（low-rank and sparse kernel）来组成一个密集kernel。基于ICGV2的基础上，做者提出了ICGV3。web 近几年，卷积网络在计算机视觉上的有效性已经获得了验证。目前卷积网络的发展主要有两个方向：一是朝着更深的方向发展，在网络各层之间增长skip connection，使得训练更深的网络成为可能；二是简化卷积网络的结构，消
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相关文章
- 1. 论文笔记-IGCV3：Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks
- 2. 【论文阅读笔记】ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks
- 3. 论文阅读笔记：MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
- 4. 【论文阅读笔记】MobileNets Efficient Convolutional Neural Networks for Mobile Vision Applications
- 5. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications论文笔记
- 6. MobileNet_v1：Efficient Convolutional Neural Networks for Mobile Vision Applications (论文笔记)
- 7. 【Learning both Weights and Connections for Efficient Neural Networks】论文笔记
- 8. 论文笔记——Aggregated Residual Transformations for Deep Neural Networks(ResNeXt)
- 9. 论文笔记——MobileNets(Efficient Convolutional Neural Networks for Mobile Vision Applications)
- 10. 论文阅读——ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks