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3Class-Gel-Segmentation-Mar-2026
Gertrude01/3Class-Gel-Segmentation-Mar-2026
3Class-Gel-Segmentation-Mar-2026 is a machine learning model from Gertrude01. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This SMP-UNet model was trained on a subset of the GelGenie training dataset (144 images). It builds upon the GelGenie-Universal-Dec-2023 model, extending it from 2-class to 3-class segmentation (background, bands, an…
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Updated Sep 4, 2026
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At a glance
- Access
- Public
- Created
- Mar 8, 2026
- Updated
- Sep 4, 2026
- SHA
- 46816298
Model card
From the Hugging Face model README
This SMP-UNet model was trained on a subset of the GelGenie training dataset (144 images). It builds upon the GelGenie-Universal-Dec-2023 model, extending it from 2-class to 3-class segmentation (background, bands, and wells).
The model was initialised from the GelGenie-Universal-Dec-2023 checkpoint and fine-tuned for 3-class segmentation from epoch 579 to epoch 650. Epoch 650 was selected as the final checkpoint.
Acknowledgements
Research supported with Cloud TPUs from Google's TPU Research Cloud (TRC).
- Created
- Mar 8, 2026
- Updated
- Sep 4, 2026