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ps3c
theodpzz/ps3c
ps3c is a machine learning model from theodpzz. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as cc-by-nc-4.0.
The project source code: GitHub Repository.
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Updated Nov 25, 2025
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At a glance
- License
- cc-by-nc-4.0
- Access
- Public
- Created
- Oct 9, 2025
- Updated
- Nov 25, 2025
- SHA
- c03d7c32
Model card
From the Hugging Face model README
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},
}
- License
- cc-by-nc-4.0
- Created
- Oct 9, 2025
- Updated
- Nov 25, 2025