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Airborne Hyperspectral Imagery for Band Selection Using Moth–Flame Metaheuristic Optimization
In this research, we study a new metaheuristic algorithm called Moth–Flame Optimization (MFO) for hyperspectral band selection. With the hundreds of highly correlated narrow spectral bands, the number of training samples required to train a statistical classifier is high. Thus, the problem is to sel...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9144346/ https://www.ncbi.nlm.nih.gov/pubmed/35621891 http://dx.doi.org/10.3390/jimaging8050126 |