Comparison Of Google Earth Engine- Based Machine Learning Classifiers For Mapping Aquaculture Ponds In Sungai Udang, Penang

This study aims to evaluate the performance of different built-in machine learning classifiers such as Random Forest (RF), Support Vector Machine (SVM), and Classification and Regression Trees (CART) to map aquaculture ponds over Sungai Udang, Penang.

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Main Author: Rajandran, Arvinth
Format: Thesis
Language:English
Published: 2023
Subjects:
Online Access:http://eprints.usm.my/60173/1/Pages%20from%20ARVINTH%20AL%20RAJANDRAN%20-%20TESIS.pdf
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Institution: Universiti Sains Malaysia
Language: English
id my.usm.eprints.60173
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spelling my.usm.eprints.60173 http://eprints.usm.my/60173/ Comparison Of Google Earth Engine- Based Machine Learning Classifiers For Mapping Aquaculture Ponds In Sungai Udang, Penang Rajandran, Arvinth H1-99 Social sciences (General) This study aims to evaluate the performance of different built-in machine learning classifiers such as Random Forest (RF), Support Vector Machine (SVM), and Classification and Regression Trees (CART) to map aquaculture ponds over Sungai Udang, Penang. 2023-02 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/60173/1/Pages%20from%20ARVINTH%20AL%20RAJANDRAN%20-%20TESIS.pdf Rajandran, Arvinth (2023) Comparison Of Google Earth Engine- Based Machine Learning Classifiers For Mapping Aquaculture Ponds In Sungai Udang, Penang. Masters thesis, Universiti Sains Malaysia.
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic H1-99 Social sciences (General)
spellingShingle H1-99 Social sciences (General)
Rajandran, Arvinth
Comparison Of Google Earth Engine- Based Machine Learning Classifiers For Mapping Aquaculture Ponds In Sungai Udang, Penang
description This study aims to evaluate the performance of different built-in machine learning classifiers such as Random Forest (RF), Support Vector Machine (SVM), and Classification and Regression Trees (CART) to map aquaculture ponds over Sungai Udang, Penang.
format Thesis
author Rajandran, Arvinth
author_facet Rajandran, Arvinth
author_sort Rajandran, Arvinth
title Comparison Of Google Earth Engine- Based Machine Learning Classifiers For Mapping Aquaculture Ponds In Sungai Udang, Penang
title_short Comparison Of Google Earth Engine- Based Machine Learning Classifiers For Mapping Aquaculture Ponds In Sungai Udang, Penang
title_full Comparison Of Google Earth Engine- Based Machine Learning Classifiers For Mapping Aquaculture Ponds In Sungai Udang, Penang
title_fullStr Comparison Of Google Earth Engine- Based Machine Learning Classifiers For Mapping Aquaculture Ponds In Sungai Udang, Penang
title_full_unstemmed Comparison Of Google Earth Engine- Based Machine Learning Classifiers For Mapping Aquaculture Ponds In Sungai Udang, Penang
title_sort comparison of google earth engine- based machine learning classifiers for mapping aquaculture ponds in sungai udang, penang
publishDate 2023
url http://eprints.usm.my/60173/1/Pages%20from%20ARVINTH%20AL%20RAJANDRAN%20-%20TESIS.pdf
http://eprints.usm.my/60173/
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