Source: Geosciences. Unidade: EP
Subjects: OURO, MINERALOGIA, MODELOS, APRENDIZADO COMPUTACIONAL
ABNT
COSTA, Fabrizzio Rodrigues e CARNEIRO, Cleyton de Carvalho e ULSEN, Carina. Enhanced gold ore classification: A comparative cnalysis of machine learning techniques with textural and chemical data. Geosciences, v. 15, 2025Tradução . . Disponível em: https://repositorio.usp.br/directbitstream/1a9a316f-d979-4068-8c20-52107e3790ef/ULSEN-2025-Enhanced_gold_ore_classification.pdf. Acesso em: 06 out. 2025.APA
Costa, F. R., Carneiro, C. de C., & Ulsen, C. (2025). Enhanced gold ore classification: A comparative cnalysis of machine learning techniques with textural and chemical data. Geosciences, 15. doi:10.3390/geosciences15070248NLM
Costa FR, Carneiro C de C, Ulsen C. Enhanced gold ore classification: A comparative cnalysis of machine learning techniques with textural and chemical data [Internet]. Geosciences. 2025 ; 15[citado 2025 out. 06 ] Available from: https://repositorio.usp.br/directbitstream/1a9a316f-d979-4068-8c20-52107e3790ef/ULSEN-2025-Enhanced_gold_ore_classification.pdfVancouver
Costa FR, Carneiro C de C, Ulsen C. Enhanced gold ore classification: A comparative cnalysis of machine learning techniques with textural and chemical data [Internet]. Geosciences. 2025 ; 15[citado 2025 out. 06 ] Available from: https://repositorio.usp.br/directbitstream/1a9a316f-d979-4068-8c20-52107e3790ef/ULSEN-2025-Enhanced_gold_ore_classification.pdf