Evaluating training data for crop type classifıcation using support vector machine and random forests

Evaluating training data for crop type classifıcation using support vector machine and random forests

This study evaluated the effectiveness of three different training datasets for crop type classification using both support vector machines (SVMs) and random forests (RFs). In supervised classification, one of the main facing challanges is to define the training set for the full representation of la...

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Bibliographic Details
Main Authors:	Mustafa Ustuner, Fusun Balik Sanli
Format:	Article
Language:	Bosnian
Published:	Union of Associations of Geodetic Professionals in Bosnia and Herzegovina 2017-12-01
Series:	Geodetski Glasnik
Subjects:	training data crop type classification support vector machines random forests machine learning
Online Access:	https://www.glasnik.suggsbih.ba/glasnik/48/documents/GG48_125.pdf

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