2019/11/08
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Note.
1. GPU
2. Max-pooling
3. 小的卷積核
4. 加深有效
5. 加寬無效
6. 只在小資料集 MNIST 與 CIFAR-10
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References
# PreVGGNet
Ciresan, Dan C., et al. "Flexible, high performance convolutional neural networks for image classification." IJCAI Proceedings-International Joint Conference on Artificial Intelligence. Vol. 22. No. 1. 2011.
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.481.4406&rep=rep1&type=pdf
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.481.4406&rep=rep1&type=pdf
深度学习论文理解3:Flexible, high performance convolutional neural networks for image classification - whiteinblue的专栏 - CSDN博客
https://blog.csdn.net/whiteinblue/article/details/43149363
[Pytorch Taipei] Paper Flexible, high performance convolutional neural networks for image classification
https://medium.com/@ChrisChou0426/pytorch-taipei-paper-flexible-high-performance-convolutional-neural-networks-for-image-4153f9495113
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