DenseNet: Densely connected convolutional network
贡献和总结 1. 使用dense block(3到4个左右), 每个dense里面的每一层和其余任意层都连接, 前面的作为输入, 输出到之后所有的. 2. 1X1卷积可以用来改变每一层的输入层数 1 introduction 设计灵感来自DCNN中信息在长距离传输中可能会丢失. dense block 结构是每一层都很其余的层连接: 当前层的输入串联之前所有层的输出特征图, 然后输出特征图串联
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相关文章
- 1. DenseNet--Densely Connected Convolutional Networks
- 2. 【DenseNet】《Densely Connected Convolutional Networks》
- 3. DenseNet Densely Connected Convolutional Networks
- 4. DenseNet——Densely Connected Convolutional Networks
- 5. Densely Connected Convolutional Networks(DenseNet)
- 6. DenseNet---《Densely Connected Convolutional Networks》
- 7. Densely Connected Convolutional Networks (DenseNet 2017 CVPR)
- 8. Ensemble of 3D densely connected convolutional network
- 9. Densely Connected Convolutional Networks
- 10. Densely Connected Convolutional Networks(2017)