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

Skip Layer - Feature Sizes #7

Open
zeynepalici opened this issue Apr 19, 2022 · 2 comments
Open

Skip Layer - Feature Sizes #7

zeynepalici opened this issue Apr 19, 2022 · 2 comments

Comments

@zeynepalici
Copy link

zeynepalici commented Apr 19, 2022

Hi,

In the related paper, the parameters encoded for a skip layer are the numbers of the feature maps for the two convolutional layers (denoted as F1 and F2, respectively). But you stated them as filter sizes and values of power of 2. I'm trying to figure out the article and implementation. Would you explain to me your point of view about that?

Thank you.

@QAQureshi
Copy link

Following.

@QAQureshi
Copy link

Hi,

In the related paper, the parameters encoded for a skip layer are the numbers of the feature maps for the two convolutional layers (denoted as F1 and F2, respectively). But you stated them as filter sizes and values of power of 2. I'm trying to figure out the article and implementation. Would you explain to me your point of view about that?

Thank you.

Here is the code link (implemented by the author of the paper) https://github.com/yn-sun/cnn-ga

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