Application of Dirichlet Process and Support Vector Machine Techniques for Mapping Alteration Zones Associated with Porphyry Copper Deposit Using ASTER Remote Sensing Imagery

Application of Dirichlet Process and Support Vector Machine Techniques for Mapping Alteration Zones Associated with Porphyry Copper Deposit Using ASTER Remote Sensing Imagery

The application of machine learning (ML) algorithms for processing remote sensing data is momentous, particularly for mapping hydrothermal alteration zones associated with porphyry copper deposits. The unsupervised Dirichlet Process (DP) and the supervised Support Vector Machine (SVM) techniques can...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Mastoureh Yousefi, Seyed Hassan Tabatabaei, Reyhaneh Rikhtehgaran, Amin Beiranvand Pour, Biswajeet Pradhan
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
Materias:
porphyry copper deposits
ASTER
machine learning
DP
SVM
SAM
Mineralogy
QE351-399.2
Acceso en línea:https://doaj.org/article/8592dc01e06644e6a1437f480d9e7e96
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!

Internet

https://doaj.org/article/8592dc01e06644e6a1437f480d9e7e96

Ejemplares similares