DC Field | Value |
dc.contributor.author | Filippo, Michel Pedro |
dc.contributor.author | Gomes, Otávio da Fonseca Martins |
dc.contributor.author | Ostwald, Gilson Alexandre |
dc.contributor.author | Costa, Pedro da |
dc.contributor.author | Mota, Guilherme Lucio Abelha |
dc.date.accessioned | 2021-10-27T14:07:16Z |
dc.date.available | 2021-10-27T14:07:16Z |
dc.date.issued | 2021 |
dc.identifier.issn | 0892-6875 |
dc.identifier.uri | https://doi.org/10.1016/j.mineng.2021.107007 |
dc.language.iso | en_US |
dc.publisher | Minerals Engineering 170 (2021) |
dc.subject | Ore characterization |
dc.subject | Image analysis |
dc.subject | Deep learning |
dc.subject | Semantic segmentation |
dc.subject | Iron ore |
dc.title | Deep learning semantic segmentation of opaque and non-opaque minerals from epoxy resin in reflected light microscopy images |
dc.type | Article |
Appears in Collections: | Artigos de Periódicos
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