DenseNet（二）：Overview

DenseNet （二）：Overview

2020/12/28

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施工中。。。

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https://pixabay.com/zh/photos/architecture-construction-sites-3254023/

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◎ Abstract

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◎ Introduction

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本論文要解決（它之前研究）的（哪些）問題（弱點）？ 

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# ResNet v2。

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◎ Method

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解決方法？ 

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# DenseNet。

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具體細節？

http://hemingwang.blogspot.com/2021/03/densenetillustrated.html

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◎ Result

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本論文成果。 

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◎ Discussion

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本論文與其他論文（成果或方法）的比較。 

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成果比較。 

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方法比較。 

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◎ Conclusion 

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◎ Future Work

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後續相關領域的研究。 

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# CSPNet

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後續延伸領域的研究。

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# Tiramisu

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◎ References

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# ResNet v2。被引用 4560 次。重點從 residual block 轉移到 pure identity mapping，網路可到千層。

He, Kaiming, et al. "Identity mappings in deep residual networks." European conference on computer vision. Springer, Cham, 2016.

https://arxiv.org/pdf/1603.05027.pdf

# DenseNet。被引用 12498 次。反覆使用 conv1 也可加深網路。

Huang, Gao, et al. "Densely connected convolutional networks." Proceedings of the IEEE conference on computer vision and pattern recognition. 2017.

https://openaccess.thecvf.com/content_cvpr_2017/papers/Huang_Densely_Connected_Convolutional_CVPR_2017_paper.pdf

# CSPNet

Wang, Chien-Yao, et al. "CSPNet: A new backbone that can enhance learning capability of CNN." Proceedings of the IEEE/CVF conference on computer vision and pattern recognition workshops. 2020.

https://openaccess.thecvf.com/content_CVPRW_2020/papers/w28/Wang_CSPNet_A_New_Backbone_That_Can_Enhance_Learning_Capability_of_CVPRW_2020_paper.pdf

# Tiramisu

Jégou, Simon, et al. "The one hundred layers tiramisu: Fully convolutional densenets for semantic segmentation." Proceedings of the IEEE conference on computer vision and pattern recognition workshops. 2017.

https://openaccess.thecvf.com/content_cvpr_2017_workshops/w13/papers/Jegou_The_One_Hundred_CVPR_2017_paper.pdf

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