IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing· 2020Q1· Review

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

Mohammadreza Sheykhmousa, Masoud Mahdianpari, Hamid Ghanbari, Fariba Mohammadimanesh et al.

1,064citations
Q1SCImago
2020year

Short summary

A meta-analysis of 251 papers reveals Random Forest (RF) outperforms Support Vector Machines (SVM) in remote sensing image classification across various data types, spatial resolutions, and feature extraction methods.

AI-generated from the title and abstract; the full text is not read.

TakeawaysIn the app

Key pointsIn the app

Ask the paperIn the app

The rest is in the Pofolia app

Takeaways, key points and questions to the paper; new summaries every day for your field. Free.

Get it on Google Play Download on the App Store

Field: Media Technology

Media TechnologyEngineering