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A 2D hyperspectral library of mineral reflectance, from 900 to 2500 nm
Mineral identification using machine learning requires a significant amount of training data. We built a library of 2D hyperspectral images of minerals. The library contains reflectance images of 130 samples, of 76 distinct minerals, with more than 3.9 million data points. In order to produce this d...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6848079/ https://www.ncbi.nlm.nih.gov/pubmed/31712558 http://dx.doi.org/10.1038/s41597-019-0261-9 |