ACTU for Magnitude Regression
This is ACTU for direction classification of MNDWI difference.
Model Details
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 tri-class mask of future MNDWI direction of change.
- Developed by: Daniele Rege Cambrin
- Model type: ACTU
- License: OpenRAIL
- Repository: Github
- Paper: Arxiv
How to Get Started with the Model
The model is integrated into Transformers, so you can easily load it with the following code:
AutoModel.from_pretrained("DarthReca/actu-direction-classification", 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 |
Training Details
The model is pre-trained on Landsat-5 images and fine-tuned on Sentinel-2 of HydroChronos.
Citation
@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},
}
Licensing
The project uses third-party software. For detailed information on the licensing of each component, please see the NOTICE.md file.
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