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  license: openrail
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  datasets:
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  - DarthReca/hydro-chronos
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- pipeline_tag: image-segmentation
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  tags:
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  - climate
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  - geospatial
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  library_name: transformers
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  ---
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- # ACTU for Magnitude Regression
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  <!-- Provide a quick summary of what the model is/does. -->
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- This is ACTU for pixelwise regression of MNDWI.
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  ## Model Details
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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 single real mask of future MNDWI.
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  - **Developed by:** Daniele Rege Cambrin
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  - **Model type:** ACTU
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  The model is integrated into Transformers, so you can easily load it with the following code:
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  ```python
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- AutoModel.from_pretrained("DarthReca/actu-magnitude-regression", trust_remote_code=True, revision=<model_type>)
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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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  ## 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.
 
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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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  library_name: transformers
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  ---
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+ # ACTU for Change Detection
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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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  ## Model Details
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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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  - **Developed by:** Daniele Rege Cambrin
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  - **Model type:** ACTU
 
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  The model is integrated into Transformers, so you can easily load it with the following code:
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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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  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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  ## 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.