Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

ESPCN's architecture #1

Closed
kligvasser opened this issue Dec 3, 2017 · 1 comment
Closed

ESPCN's architecture #1

kligvasser opened this issue Dec 3, 2017 · 1 comment

Comments

@kligvasser
Copy link

The suggested model is a bit different than the on in the paper. You got 4 convolutional layers, whereas, there are only 3 in the paper. Have you tried less? Why do you have sigmoid in the output layer?
Thank you very much!
Idan

@leftthomas
Copy link
Owner

@kligvasser , you could change that model, it's easy, I use sigmoid to make sure the output image value is between [0,1], you also could use tanh to the last layer, and add 1 then div it by 2 to make sure it between [0,1].

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants