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Efficient Unsupervised Classification of Hyperspectral Images Using Voronoi Diagrams and Strong Patterns
Hyperspectral images (HSIs) are a powerful tool to classify the elements from an area of interest by their spectral signature. In this paper, we propose an efficient method to classify hyperspectral data using Voronoi diagrams and strong patterns in the absence of ground truth. HSI processing consum...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7582408/ https://www.ncbi.nlm.nih.gov/pubmed/33027997 http://dx.doi.org/10.3390/s20195684 |