A Robust Occlusion-Aware Deep Learning Architecture for Thermal Aerial Person Classification in Search-and-Rescue Missions
Uncrewed aerial vehicles equipped with long-wave infrared cameras are a promising tool for locating missing persons, yet their performance collapses when more than 70% of a human body is obscured by vegetation. We address this limitation by reformulating the task as a thermal classification problem...
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| Autores principales: | , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
IEEE
2026-01-01
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| Colección: | IEEE Access |
| Materias: | |
| Acceso en línea: | https://ieeexplore.ieee.org/document/11357877/ |
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