Densely Connected Convolutional Networks 论文笔记
0 摘要 最近的成果显示，如果神经网络各层到输入和输出层采用更短的连接，那么网络可以设计的更深、更准确且训练起来更有效率。本文根据这个现象，提出了Dense Convolutional Network (DenseNet)，它以前馈的方式将每个层都连接到其他每一层。然而传统的 L L 层卷积神经网络有 L L 连接（每一层与其后面的一层相连接），而DenseNet的任一层不仅与相邻层有连接
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相关文章
- 1. 论文笔记Densely Connected Convolutional Networks v1
- 2. 【论文阅读笔记】Densely Connected Convolutional Networks
- 3. 论文笔记——Densely Connected Convolutional Networks(DenseNet)
- 4. 论文笔记：Densely Connected Convolutional Networks
- 5. Densely Connected Convolutional Networks
- 6. 【DenseNet】《Densely Connected Convolutional Networks》
- 7. DenseNet---《Densely Connected Convolutional Networks》
- 8. Densely Connected Convolutional Networks(2017)
- 9. DenseNet Densely Connected Convolutional Networks
- 10. Densely Connected Convolutional Networks(DenseNet)