ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation笔记
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation (a)是intial block。Input为512x512。Num_filters为13，max_pool为2x2，s=2，concat变成16x512x512 (b)bottleneck module：1x1conv reduce dim +
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相关文章
- 1. 【阅读笔记】《ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation》
- 2. 《ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation》论文笔记
- 3. ENet: A deep neural network architecture for real-time semantic segmentation
- 4. 论文阅读：ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
- 5. ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
- 6. ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation----2016年 论文翻译解读
- 7. 【图像分割论文阅读】ENet：A Deep Neural Network Architecture for Real-Time Semantic Segmentation
- 8. 【阅读笔记】《ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation》
- 9. 论文笔记：ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation
- 10. 论文笔记：Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation