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						--- | 
					
					
						
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						license: openrail | 
					
					
						
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						datasets: | 
					
					
						
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						- DarthReca/hydro-chronos | 
					
					
						
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						tags: | 
					
					
						
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						- climate | 
					
					
						
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						- geospatial | 
					
					
						
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						- remote-sensing | 
					
					
						
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						- spatiotemporal | 
					
					
						
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						- multi-modal | 
					
					
						
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						- earth-observation | 
					
					
						
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						- time-series | 
					
					
						
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						- hydrology | 
					
					
						
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						library_name: transformers | 
					
					
						
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						pipeline_tag: image-segmentation | 
					
					
						
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						--- | 
					
					
						
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						 | 
					
					
						
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						# ACTU for Change Detection | 
					
					
						
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 | 
					
					
						
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						<!-- Provide a quick summary of what the model is/does. --> | 
					
					
						
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						This is ACTU for change detection of thresholded absolute MNDWI difference. | 
					
					
						
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 | 
					
					
						
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						## Model Details | 
					
					
						
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 | 
					
					
						
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						<!-- Provide a longer summary of what this model is. --> | 
					
					
						
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						This architecture is a temporal UNet (with ConvLSTMs), featuring an LSTM branch to process climate timeseries and a gating mechanism.  | 
					
					
						
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						It is designed to receive a timeseries of Sentinel-2 images, DEM, and timeseries of climate variables and output a binary mask. | 
					
					
						
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 | 
					
					
						
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						- **Developed by:** Daniele Rege Cambrin | 
					
					
						
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						- **Model type:** ACTU | 
					
					
						
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						- **License:** OpenRAIL | 
					
					
						
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						- **Repository:** [Github](https://github.com/DarthReca/hydro-chronos) | 
					
					
						
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						- **Paper:** [Arxiv](https://arxiv.org/abs/2506.14362) | 
					
					
						
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 | 
					
					
						
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 | 
					
					
						
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						## How to Get Started with the Model | 
					
					
						
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						The model is integrated into Transformers, so you can easily load it with the following code: | 
					
					
						
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 | 
					
					
						
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						```python | 
					
					
						
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						AutoModel.from_pretrained("DarthReca/actu-change-detection", trust_remote_code=True, revision=<model_type>) | 
					
					
						
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						``` | 
					
					
						
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 | 
					
					
						
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						Load the model with the desired configuration with the *revision* parameter (the branches of this repo). These configurations are available: | 
					
					
						
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 | 
					
					
						
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						| Revision    | Backbone        | DEM | Climate | | 
					
					
						
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						|-------------|-----------------|:---:|:-------:| | 
					
					
						
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						| main        | ConvNeXtV2 Base |  No  |    No    | | 
					
					
						
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						| dem-climate | ConvNeXtV2 Base |  Yes  |    Yes    | | 
					
					
						
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 | 
					
					
						
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						## Training Details | 
					
					
						
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						The model is pre-trained on Landsat-5 images and fine-tuned on Sentinel-2 of HydroChronos. | 
					
					
						
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						## Citation | 
					
					
						
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						```bibtex | 
					
					
						
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						@misc{cambrin2025hydrochronosforecastingdecadessurface, | 
					
					
						
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						      title={HydroChronos: Forecasting Decades of Surface Water Change},  | 
					
					
						
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						      author={Daniele Rege Cambrin and Eleonora Poeta and Eliana Pastor and Isaac Corley and Tania Cerquitelli and Elena Baralis and Paolo Garza}, | 
					
					
						
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						      year={2025}, | 
					
					
						
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						      eprint={2506.14362}, | 
					
					
						
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						      archivePrefix={arXiv}, | 
					
					
						
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						      primaryClass={cs.CV}, | 
					
					
						
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						      url={https://arxiv.org/abs/2506.14362},  | 
					
					
						
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						} | 
					
					
						
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						``` | 
					
					
						
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 | 
					
					
						
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						## Licensing | 
					
					
						
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						The project uses third-party software. For detailed information on the licensing of each component, please see the [**NOTICE.md**](NOTICE.md) file. |