Skip to content

theblackcat102/dynamic-routing-capsule-cifar

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

26 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

dynamic-routing-capsule-cifar

reference from : https://github.com/XifengGuo/CapsNet-Keras

Testing Cifar-10 datasets using Dynamic Routing between Capsules

This data will be compared with resnet18(18 layers deep) which contain a similar parameters with the tested capsule net in Hinton's paper.

Each epoch only takes less than 5 minutes in resnet, so I left it to train for over 100 epoch, which checkpoint stops at epoch 44 Resnet

Each epoch in capsule net takes about 30 minutes, in this case, I only left it training for 60 epoch. Capsule

In the end, resnet yield an accuracy of 0.8231, while the "simple" capsule net only 0.7307

Here is the reconstruction result from the capsule decoder(3 fully connected layers). I suspect the bad reconstruction was due to simple FC network rather than using Image GAN structure of stacking Maxpooling(oops) and convolution layer. According to the paper, this addition reconstruction section contribute quite a significant increase in the final accuracy. In my opinion, it really doesn't makes sense, since the major study here was to evaluate the performance of capsule structure.

Reconstruction