-
Notifications
You must be signed in to change notification settings - Fork 3
Description
Thank you for your impressive work on ZAugNet/ZAugNet+. We found the methodology of using knowledge distillation for self-supervised axial augmentation highly innovative in axial super-resolution task.
We are currently conducting a comprehensive benchmark of several axial super-resolution methods. While your repository provides excellent code and some sample data in zenodo, we are having difficulty locating the High-Resolution (HR) ground truth datasets used for the quantitative results in your paper (specifically the Ascidian embryo, Filament, Nuclei, and Human datasets).
To ensure a fair and rigorous comparison, we would like to request access to:
The high-resolution versions of the Ascidian embryo dataset.
The HR ground truth for the synthetic Filament, Nuclei, and Human datasets used in your benchmarking.
If these datasets are already hosted publicly elsewhere, could you please point us to the correct repository or download link? If they are not yet public, do you have plans to release them, or would you be open to sharing them for research comparison purposes?
Having access to these standardized HR volumes is crucial for the bio-imaging community to maintain a consistent benchmarking standard for new axial enhancement algorithms.
Thank you for your time and for your contribution to the field!