Advanced Mineral Deposit Mapping via Deep Learning and SVM Integration With Remote Sensing Imaging Data
ABSTRACT Automating mineral delineation and rock type analysis using remote sensing imaging data is a critical application of machine learning. Traditional machine learning methods often struggle with accuracy and precise map generation. This study aims to enhance performance through a refined deep...
Saved in:
Main Authors: | Nazir Jan, Nasru Minallah, Madiha Sher, Muhammad Wasim, Shahid Khan, Amal Al‐Rasheed, Hazrat Ali |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2025-01-01
|
Series: | Engineering Reports |
Subjects: | |
Online Access: | https://doi.org/10.1002/eng2.13031 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Seasonal Land Use and Land Cover Mapping in South American Agricultural Watersheds Using Multisource Remote Sensing: The Case of Cuenca Laguna Merín, Uruguay
by: Giancarlo Alciaturi, et al.
Published: (2025-01-01) -
FORECASTING OF POTATO YIELD ESTIMATION BY SATELLITE BASED REMOTE SENSING TECHNIQUE
by: Mohammad Mukhlesur Rahman, et al.
Published: (2024-05-01) -
Optimizing SVM for argan tree classification using Sentinel-2 data: A case study in the Sous-Massa Region, Morocco
by: Abdelhak El Kharki, et al.
Published: (2024-11-01) -
Estimation of Dendrocalamus giganteus leaf area index by combining multi-source remote sensing data and machine learning optimization model
by: Zhen Qin, et al.
Published: (2025-01-01) -
Satellite remote sensing and the integration of 6G communication and remote sensing
by: Wenjia XU, et al.
Published: (2023-04-01)