---
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