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# What Makes ResNet Good Model? | snoop2head's blog
Residual Connection is Good, Up to Now ResNet was introduced in 2015 on the paper Deep Residual Learning for Image Recognition. Nevertheless, resid…
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### Reasoning
Skip layers help to mitigate vanishing gradient problem. They are a fundamental part of many modern neural networks.
### Prior Art
(https://www.tensorflow.org/api_docs/python/tf/keras…
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- https://arxiv.org/abs/2102.07870v2
- 2021
バックプロパゲーションを用いた深い残差ニューラルネットワーク（ResNets）の学習には、ネットワークの深さに応じて線形に増加するメモリコストがかかります。
この問題を回避する方法として、可逆的なアーキテクチャを使用することが挙げられる。
本論文では、モーメンタム項を追加することで、ResNetの順…
e4exp updated
3 years ago
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**Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is. Ex. I’m always frustrated when […]
Hello, I am trying to resolve Euler'…
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# Aggregated Residual Transformations for Deep Neural Networks #
- Author: Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, Kaiming He
- Origin: https://arxiv.org/abs/1611.05431
- Related:
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https://github.com/facebookresearch/ResNeXt
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**Description:** The current Convolutional Neural Network (CNN) model for terrain classification is functional, but there are several areas for improvement to boost performance and efficiency. These o…
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https://arxiv.org/abs/1512.03385
> Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than t…
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**Is your feature request related to a problem? Please describe.**
A clear and concise description of what the problem is.
Yes, Image Super-Resolution (ISR) is directly related to solving specific…
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Read the papers in [Deep Learning’s Most Important Ideas](https://www.kdnuggets.com/2020/09/deep-learnings-most-important-ideas.html).
- [x] Tackling ImageNet with AlexNet and Dropout
- [x] [I…