Comparative analysis of support vector machine, maximum likelihood and neural network classification on multispectral remote sensing data

Comparative analysis of support vector machine, maximum likelihood and neural network classification on multispectral remote sensing data

Land cover classification is an essential process in many remote sensing applications. Classification based on supervised methods have been preferred by many due to its practicality, accuracy and objectivity compared to unsupervised methods. Nevertheless, the performance of different supervised meth...

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Bibliographic Details
Main Authors: Ahmad, Asmala, Mohd Hashim, Ummi Kalsom, Mohd, Othman, Abdullah, Mohd Mawardy, Sakidin, Hamzah, Rasib, Abd Wahid, Sufahani, Suliadi Firdaus
Format: Article
Language:English
Published: The Science and Information (SAI) Organization Limited 2018
Subjects:
QA75 Electronic computers. Computer science
TP200-248 Chemicals: Manufacture, use, etc.
Online Access:http://eprints.uthm.edu.my/3552/
http://eprints.uthm.edu.my/3552/1/AJ%202018%20%28700%29%20Comparative%20analysis%20of%20support%20vector%20machine%2C%20maximum%20likelihood%20and%20neural%20network%20classification%20on%20multispectral%20remote%20sensing%20data.pdf

Internet

http://eprints.uthm.edu.my/3552/
http://eprints.uthm.edu.my/3552/1/AJ%202018%20%28700%29%20Comparative%20analysis%20of%20support%20vector%20machine%2C%20maximum%20likelihood%20and%20neural%20network%20classification%20on%20multispectral%20remote%20sensing%20data.pdf

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