Evaluating the Performance of Machine Learning and Deep Learning Techniques to HyMap Imagery for Lithological Mapping in a Semi-Arid Region: Case Study from Western Anti-Atlas, Morocco

Evaluating the Performance of Machine Learning and Deep Learning Techniques to HyMap Imagery for Lithological Mapping in a Semi-Arid Region: Case Study from Western Anti-Atlas, Morocco

Accurate lithological mapping is a crucial juncture for geological studies and mineral exploration. Hyperspectral data provide the opportunity to extract detailed information about the geology and mineralogy of the Earth’s surface. Machine learning (ML) and deep learning (DL) techniques provide an a...

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Bibliographic Details
Main Authors: Soufiane Hajaj, Abderrazak El Harti, Amine Jellouli, Amin Beiranvand Pour, Saloua Mnissar Himyari, Abderrazak Hamzaoui, Mazlan Hashim
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Minerals
Subjects:
HyMap imagery
lithological mapping
machine learning
CNN
KNN
RF
Online Access:https://www.mdpi.com/2075-163X/13/6/766

Internet

https://www.mdpi.com/2075-163X/13/6/766

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