Land Cover Classification Using Extremely Randomized Trees: A Kernel Perspective

Dataset

Description

In this research works (2 papers), we evaluate the pros and cons of using tree-based kernels (Random Forest Kernels and Extra-Trees Kernels) in an SVM compared to using the conventional Radial Basis Function (RBF) kernel, standard Random Forest, and standard Extra-Trees classifier. A time series of seven multispectralWorldView-2 images acquired over Sukumba (Mali) are used to illustrate these studies.
Date made available4 Feb 2020
PublisherDANS easy
Date of data production3 Feb 2020

Cite this

Zafari, A. (Creator) (4 Feb 2020). Land Cover Classification Using Extremely Randomized Trees: A Kernel Perspective. DANS easy. 10.17026/dans-247-y9x3