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`Messis`is a crop classification model for Switzerland, trained on the ZueriCrop 2.0 dataset. It is fine-tuned from the Prithvi geospatial foundation model, optimized for high-resolution Sentinel-2 imagery specific to Swiss agricultural landscapes. Messis leverages a hierarchical label structure and pretrained weights.
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### Key Features
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1. **Adapted for High-Resolution Crop Classification:** Messis is fine-tuned from the Prithvi geospatial foundation model, originally trained on U.S. data, and optimized for high-resolution Sentinel-2 imagery specific to Swiss agricultural landscapes.
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2. **Leveraged Hierarchical Label Structure:** Utilizes a remote-sensing-focused hierarchical label structure, enabling more accurate classification across multiple levels of crop granularity.
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`Messis`is a crop classification model for Switzerland, trained on the ZueriCrop 2.0 dataset. It is fine-tuned from the Prithvi geospatial foundation model, optimized for high-resolution Sentinel-2 imagery specific to Swiss agricultural landscapes. Messis leverages a hierarchical label structure and pretrained weights.
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### Key Features
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1. **Adapted for High-Resolution Crop Classification:** Messis is fine-tuned from the Prithvi geospatial foundation model, originally trained on U.S. data, and optimized for high-resolution Sentinel-2 imagery specific to Swiss agricultural landscapes.
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2. **Leveraged Hierarchical Label Structure:** Utilizes a remote-sensing-focused hierarchical label structure, enabling more accurate classification across multiple levels of crop granularity.
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