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---
license: mit
base_model:
- google/efficientnet-b3
---
# gapclosure-quantify-unet
This repository contains the trained models for automated scratch assay quantification,
allowing to the timelapse imaging of collective epithelial cell migration in a timely
fashion.
It employs a U-Net EfficientNet-B3 architecture, and is trained on 173 images
with a validation set of about 35 images.
## Details
Scripts can be found on this [GitHub Repository](https://github.com/nwoodweb/gapclosure-quantify.git)
LAST UPDATE: 1635 UTC 27 JULY 2026