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This is a SE_DenseNet which contains a senet (Squeeze-and-Excitation Networks by Jie Hu, Li Shen, and Gang Sun) module, written in Pytorch, train, and eval codes have been released.

Home Page: https://zhuanlan.zhihu.com/p/48499356

License: MIT License

Python 100.00%
senet pytorch densenet cnn-classification squeeze-and-excitation

se_densenet's Issues

More variant architecture of se_densnet need to try and test

Hi, thanks for sharing your experiment results. I checked and found that you may have some redundant code in the _Dense layer that adds thr seblock in of convolution. You added it in loop (for) and after first convolution. Why do you add seblock in _Dense_layer again? Thanks

Amount of parameters

Hi) Thank you for your great work!
Could you show an amount of model parameters? I'm trying to implement SE-DenseNet from the scratch for my diploma work and I am not sure that my SE implementation is correct (it adds more than 3 millions parameters...)

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