metadata
license: cc-by-nc-4.0
An Ensemble-based Two-step Framework for Classification of Pap Smear Cell Images
Code repository
The project source code: GitHub Repository.
Available resources
Train weights for Step 1 and Step 2, as well as the per-class final predicted probabilities, are provided in this repository.
PS3C
This project was developed as part of the PS3C Challenge at ISBI 2025.
Kaggle Challenge: Kaggle Link.
APACC Dataset original paper: Paper access.
Citation
If you use this model or related resources, we would appreciate the following citation:
@inproceedings{dipiazza2025ps3c,
author = {Di Piazza Theo and Loic Boussel},
title = {An Ensemble-based Two-step Framework for Classification of Pap Smear Cell Images},
booktitle = {Proceedings of the IEEE International Symposium on Biomedical Imaging (ISBI)},
year = {2025},
organization = {IEEE},
}