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The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation_2016
时间 2021-01-11
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作者:Simon Jégou Michal Drozdzal David Vazquez .. Abstract 典型的语义分割架构由(a)一条下采样路径,负责提取粗的语义特征,再加一个(b)一条上采样路径,负责回复图像分辨率,(c)和一个可选的后处理模块(比如,条件随机场)来精调模型预测。 最近一个新的架构DenseNets,主意来源于:如果每层直接连接其他层,就像前馈机制一样,网络会变得更精确
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相关文章
1.
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
2.
图像分割“The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation”
3.
【图像分割论文阅读】The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
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The One Hundred Layers Tiramisu:Fully Convolutional DenseNets for Semantic Segmentation手动翻译
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