Simplified SqueezeNet

My research experiments on speeding up the training stage of deep learning network SqueezeNet was successful. I improved SqueezeNet by simplifying its architecture Simplified_SqueezeNet.

The speedup gain was about 4 times faster than SqueezeNet. I conducted my experiments on two large scale image datasets. The used datasets are MIT Places205 and MIT Places2. Simplified_SqueezeNet got higher accuracy on both Top-1 and Top-5 on both datasets. Your suggestions and contributions to port the networks weights and architecture to PyTorch are highly appreciated. You can find the network details in this repo:

Here’s a link to the official SqueezeNet implementation. It might be a good starting point for you.

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