Support vector machine versus random forest for remote sensing image classification: A meta-analysis and systematic review
M Sheykhmousa, M Mahdianpari… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Several machine-learning algorithms have been proposed for remote sensing image
classification during the past two decades. Among these machine learning algorithms …
classification during the past two decades. Among these machine learning algorithms …
Land-use land-cover classification by machine learning classifiers for satellite observations—A review
Rapid and uncontrolled population growth along with economic and industrial development,
especially in develo** countries during the late twentieth and early twenty-first centuries …
especially in develo** countries during the late twentieth and early twenty-first centuries …
Comparison of random forest and support vector machine classifiers for regional land cover map** using coarse resolution FY-3C images
T Adugna, W Xu, J Fan - Remote Sensing, 2022 - mdpi.com
The type of algorithm employed to classify remote sensing imageries plays a great role in
affecting the accuracy. In recent decades, machine learning (ML) has received great …
affecting the accuracy. In recent decades, machine learning (ML) has received great …
Implementation of machine-learning classification in remote sensing: An applied review
Machine learning offers the potential for effective and efficient classification of remotely
sensed imagery. The strengths of machine learning include the capacity to handle data of …
sensed imagery. The strengths of machine learning include the capacity to handle data of …
Comparison of random forest, k-nearest neighbor, and support vector machine classifiers for land cover classification using Sentinel-2 imagery
P Thanh Noi, M Kappas - Sensors, 2017 - mdpi.com
In previous classification studies, three non-parametric classifiers, Random Forest (RF), k-
Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost …
Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost …
Recent progress in semantic image segmentation
Semantic image segmentation, which becomes one of the key applications in image
processing and computer vision domain, has been used in multiple domains such as …
processing and computer vision domain, has been used in multiple domains such as …
Application of support vector machine models for forecasting solar and wind energy resources: A review
Conventional fossil fuels are depleting daily due to the growing human population. Previous
research has proved that renewable energy sources, especially solar and wind, can be …
research has proved that renewable energy sources, especially solar and wind, can be …
[HTML][HTML] Basic tenets of classification algorithms K-nearest-neighbor, support vector machine, random forest and neural network: A review
In this paper, sixty-eight research articles published between 2000 and 2017 as well as
textbooks which employed four classification algorithms: K-Nearest-Neighbor (KNN) …
textbooks which employed four classification algorithms: K-Nearest-Neighbor (KNN) …
Why Cohen's Kappa should be avoided as performance measure in classification
We show that Cohen's Kappa and Matthews Correlation Coefficient (MCC), both extended
and contrasted measures of performance in multi-class classification, are correlated in most …
and contrasted measures of performance in multi-class classification, are correlated in most …
Machine learning classification of mediterranean forest habitats in google earth engine based on seasonal sentinel-2 time-series and input image composition …
The sustainable management of natural heritage is presently considered a global strategic
issue. Owing to the ever-growing availability of free data and software, remote sensing (RS) …
issue. Owing to the ever-growing availability of free data and software, remote sensing (RS) …