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SENet.pytorch

An implementation of SENet, proposed in Squeeze-and-Excitation Networks by Jie Hu, Li Shen and Gang Sun, who are the winners of ILSVRC 2017 classification competition.

Now SE-ResNet (18, 34, 50, 101, 152) and SE-Inception-v3 are implemented.

python exec.py runs SE-ResNet50 with Cifar10 dataset.

For SE-Inception-v3, the input size is required to be 299x299 as original Inception.

references

paper authors' Caffe implementation

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PyTorch implementation of SENet

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  • Python 100.0%