Densely Connected Convolution network笔记
1、摘要部分 卷积网络现在做得越来越深，精确，并且训练起来越来越高效。本文根据这一个结论，提出了一种稠密卷积神经网络(DenseNet)。传统的L层卷积神经网络又L个连接——位于每一层和它后面一层，而我们的神经网络有，对于每一层，其输入的特征是之前的所有层，而它自己的输出特征则作为之后所有层的输入。 2、Advantage alleviate the vanishing-gradient prob
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相关文章
- 1. DenseNet: Densely connected convolutional network
- 2. Ensemble of 3D densely connected convolutional network
- 3. DenseNet--Densely Connected Convolutional Networks
- 4. 【DenseNet】《Densely Connected Convolutional Networks》
- 5. 《Densely Connected Convolutional Networks》阅读笔记
- 6. DenseNet(Densely Connected Convolutional Networks)学习笔记
- 7. 《Densely Connected Hierarchical Network for Image Denoising》阅读笔记
- 8. 【Network Architecture】Densely Connected Convolutional Networks 论文解析
- 9. 【operations】Non-local Neural Network&Densely Connected CNN
- 10. 论文笔记Densely Connected Convolutional Networks v1