metadata
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
LAST UPDATE: 1635 UTC 27 JULY 2026