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

Hello! Author, I am very sorry for taking up your precious time. Recently, I am studying one of your papers-PraNet: Parallel Reverse Attention Network for Polyp Segmentation. In the process of learning PraNet network, there is a question that has puzzled me. The problem is as follows: In the Loss Function section of Section 2.3, ' the weighted IoU loss and binary cross entropy (BCE) loss for the global restriction and local (pixel-level) restriction.' What do "global restriction and local restriction" mean exactly? Thank you! #59

Open
Progressiveyouth opened this issue Apr 17, 2023 · 1 comment

Comments

@Progressiveyouth
Copy link

No description provided.

@GewelsJI
Copy link
Collaborator

GewelsJI commented Aug 9, 2023

Good question here. You can understand them as:

  • 'global' in weighted IOU loss means that IoU can focus on structural info
  • 'local' in BCE loss means that pixel-wise restrictions between gt and pred

Best

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