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

Compared with the indicators #2

Open
wangmingaaaaa opened this issue Jul 16, 2023 · 1 comment
Open

Compared with the indicators #2

wangmingaaaaa opened this issue Jul 16, 2023 · 1 comment

Comments

@wangmingaaaaa
Copy link

Hi, I would like to ask why your paper is not related to the Enhancing Pseudo Label Quality for Semi-Supervised Domain-Generalized in 2022 Compared with the indicators of Medical Image Segmentation, is it because the backbone is different?

@xxxliu95
Copy link
Member

xxxliu95 commented Aug 9, 2023

Hi, yes, the paper you mentioned used a pre-trained ResNet as the backbone.

See in the related work:
Following \cite{liu2021semi}, Yao et al.\ \cite{yao2022enhancing} adopted a pre-trained ResNet \cite{he2016deep} as a backbone feature extractor and augmented the source data by mixing MRI images in the Fourier domain and employed pseudo-labelling to leverage the unlabelled data.

Different backbones affect the DG performance.

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