Improvements in Sample Selection Methods for Image Classification

Improvements in Sample Selection Methods for Image Classification

Traditional image classification algorithms are mainly divided into unsupervised and supervised paradigms. In the first paradigm, algorithms are designed to automatically estimate the classes’ distributions in the feature space. The second paradigm depends on the knowledge of a domain expert to iden...

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Bibliographic Details
Main Authors: Thales Sehn Körting, Leila Maria Garcia Fonseca, Emiliano Ferreira Castejon, Laercio Massaru Namikawa
Format: Article
Language:English
Published: MDPI AG 2014-08-01
Series:Remote Sensing
Subjects:
image classification
sample selection
remote sensing
Graphical User Interface (GUI)
Online Access:http://www.mdpi.com/2072-4292/6/8/7580

Internet

http://www.mdpi.com/2072-4292/6/8/7580

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