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DarthReca/actu-magnitude-regression
actu-magnitude-regression is a image segmentation model from DarthReca. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as openrail.
This is ACTU for pixelwise regression of MNDWI.
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From the Hugging Face model README
This is ACTU for pixelwise regression of MNDWI.
This architecture is a temporal UNet (with ConvLSTMs), featuring an LSTM branch to process climate timeseries and a gating mechanism. It is designed to receive a timeseries of Sentinel-2 images, DEM, and timeseries of climate variables and output a single real mask of future MNDWI.
The model is integrated into Transformers, so you can easily load it with the following code:
AutoModel.from_pretrained("DarthReca/actu-magnitude-regression", trust_remote_code=True, revision=<model_type>)
Load the model with the desired configuration with the revision parameter (the branches of this repo). These configurations are available:
| Revision | Backbone | DEM | Climate |
|---|---|---|---|
| main | ConvNeXtV2 Base | No | No |
| dem-climate | ConvNeXtV2 Base | Yes | Yes |
The model is pre-trained on Landsat-5 images and fine-tuned on Sentinel-2 of HydroChronos.
@misc{cambrin2025hydrochronosforecastingdecadessurface,
title={HydroChronos: Forecasting Decades of Surface Water Change},
author={Daniele Rege Cambrin and Eleonora Poeta and Eliana Pastor and Isaac Corley and Tania Cerquitelli and Elena Baralis and Paolo Garza},
year={2025},
eprint={2506.14362},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2506.14362},
}
The project uses third-party software. For detailed information on the licensing of each component, please see the NOTICE.md file.