Non-local U-Nets for Biomedical Image Segmentation
code tensorflow Non-local 由三个部分组成： U-Net、Residual Blocks、Global Aggregation Block U-Net 作者将原始u-net的concatenation -> sum的原因： 求和不会增加特征图的数量，因此会减少下一层中可训练参数的数量。 具有求和的skip connection可以被视为远程残差连接，可以促进模型的训练。 最
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相关文章
- 1. Paper | U-Net: Convolutional Networks for Biomedical Image Segmentation
- 2. [U-Net] U-Net: Convolutional Networks for Biomedical Image Segmentation
- 3. U-Net: Convolutional Networks for Biomedical Image Segmentation翻译
- 4. U-Net: Convolutional Networks for Biomedical Image Segmentation
- 5. Context-Aware U-Net for Biomedical Image Segmentation
- 6. [U-Net]Convolutional Networks for Biomedical Image Segmentation
- 7. 【论文学习】Non-local U-Nets for Biomedical Image Segmentation
- 8. 【Semantic Segmentation】U-Net: Convolutional Networks for Biomedical Image Segmentation 论文解析(转)...
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