LinkNet with Pretrained Encoder and Dilated Convolution for HighResolution Satellite Image

时间 2020-12-30

标签语义分割论文笔记繁體版

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Abstract D-LinkNet语义分割神经网络它采用encoder-decoder的结构、空洞卷积（dilated convolution）和预训练编码器（pretrained encoder）来完成道路提取任务。该网络采用LinkNet结构，中心部分具有空洞卷积层（dilated convolution）。Linknet结构在计算和存储方面是高效的。空洞卷积是一种在不降低特征图分辨率的前提

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1. 论文解读：D-LinkNet ：LinkNet with Pretrained Encoder and Dilated Convolution for High Resolution Satelli
2. 道路分割论文研读之D-LinkNet ：LinkNet with Pretrained Encoder and Dilated Convolution for High Resolution Sate
3. Encoder-Decoder-with-Atrous-Separable-Convolution-for-Semantic-Image-Segmentation
4. 00037-Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
5. 基于深度学习的实现影像地图道路提取
6. Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation (DeepLab v3+) 论文笔记
7. 《Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation》论文笔记
8. DeepLab_v3+:Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
9. DeepLab V3+——Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
10. 《DeepLab v3+：Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation》论文笔记

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