Video-Native Koopman Operator Learning for Active Wildfire Risk Mapping
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| Formato: | Recurso digital |
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2025
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| _version_ | 1866901234696323072 |
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| author | Achyuta, Sesha |
| author_facet | Achyuta, Sesha |
| contents | <p>stress, wind forcing, and terrain geometry. Traditional remote sensing and computer vision</p> <p>approaches rely on static imagery, episodic revisits, or purely data-driven models that struggle</p> <p>with non-stationarity, smoke occlusion, and real-time operational constraints.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17917575 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Video-Native Koopman Operator Learning for Active Wildfire Risk Mapping Achyuta, Sesha <p>stress, wind forcing, and terrain geometry. Traditional remote sensing and computer vision</p> <p>approaches rely on static imagery, episodic revisits, or purely data-driven models that struggle</p> <p>with non-stationarity, smoke occlusion, and real-time operational constraints.</p> |
| title | Video-Native Koopman Operator Learning for Active Wildfire Risk Mapping |
| url | https://doi.org/10.5281/zenodo.17917575 |