Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review

Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review

Several machine-learning algorithms have been proposed for remote sensing image classification during the past two decades. Among these machine learning algorithms, Random Forest (RF) and Support Vector Machines (SVM) have drawn attention to image classification in several remote sensing application...

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Bibliographic Details
Main Authors: Mohammadreza Sheykhmousa, Masoud Mahdianpari, Hamid Ghanbari, Fariba Mohammadimanesh, Pedram Ghamisi, Saeid Homayouni
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Image classification
meta-analysis
random forest (RF)
remote sensing (RS)
support vector machine (SVM)
Online Access:https://ieeexplore.ieee.org/document/9206124/

Internet

https://ieeexplore.ieee.org/document/9206124/

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