ResNet-D

ResNet-D

2019/11/12

前言：

論文《Deep networks with stochastic depth》，我將其命名為 ResNet-D，取其名稱中的 depth。此外，論文裡的實驗隨機丟棄一些殘差層來訓練網路，使用的技巧是 dropout。經由這樣的設計，也可將原始的殘差網路從一百層提升到一千層。

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// Review  Stochastic Depth (Image Classification) - Towards Data Science

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// Review  Stochastic Depth (Image Classification) - Towards Data Science

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// Review  Stochastic Depth (Image Classification) - Towards Data Science

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// Review  Stochastic Depth (Image Classification) - Towards Data Science

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# ResNet-D

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# ResNet-D

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# ResNet-D

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# ResNet-D

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# ResNet-D

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# ResNet-D

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# ResNet-D

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# ResNet-D

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# ResNet-D

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# ResNet-D

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# ResNet-D

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# ResNet-D

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# ResNet-D

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References

◎ 論文 

# ResNet-D

Huang, Gao, et al. "Deep networks with stochastic depth." European conference on computer vision. Springer, Cham, 2016.

https://arxiv.org/pdf/1603.09382.pdf 

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◎ 英文參考資料

Review  Stochastic Depth (Image Classification) - Towards Data Science
https://towardsdatascience.com/review-stochastic-depth-image-classification-a4e225807f4a

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◎ 簡體中文參考資料

Deep Networks with Stochastic Depth
https://bingning.wang/research/Article/?id=59