Classification of IR Images of Small Eruptions at the Erebus Volcano, Antarctica, with Zernike moments and Support Vector Machine

This repository provides an"SVM_binary_classification" Jupyter notebook and different data folders fortraining and generalization in a binary classification task using a combination ofsupport vector classifier and Zernike moments. Using a python script in the jupyter notebook and a Zernike...

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Main Authors: Honarbakhsh,Leila, Morra, Gabriele
Format: Article in Journal/Newspaper
Language:unknown
Published: Zenodo 2022
Subjects:
Antarc*
Antarctica
Online Access:https://doi.org/10.5281/zenodo.7149379
id ftzenodo:oai:zenodo.org:7149379
record_format openpolar
spelling ftzenodo:oai:zenodo.org:7149379 2024-09-15T17:43:30+00:00 Classification of IR Images of Small Eruptions at the Erebus Volcano, Antarctica, with Zernike moments and Support Vector Machine Honarbakhsh,Leila Morra, Gabriele 2022-10-05 https://doi.org/10.5281/zenodo.7149379 unknown Zenodo https://doi.org/10.5281/zenodo.7149377 https://doi.org/10.5281/zenodo.7149379 oai:zenodo.org:7149379 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode info:eu-repo/semantics/article 2022 ftzenodo https://doi.org/10.5281/zenodo.714937910.5281/zenodo.7149377 2024-07-26T19:05:22Z This repository provides an"SVM_binary_classification" Jupyter notebook and different data folders fortraining and generalization in a binary classification task using a combination ofsupport vector classifier and Zernike moments. Using a python script in the jupyter notebook and a Zernike momentfile inside eachfolder, one can classify generalizationimages in any two classes among eruption, no-eruption, and non-explosive small events (NESE). It is notable that, the SVM needs to be trained initiallyusing the Zernike moments inside the training data folders. There is also spatial and temporal information on NESEs in December 2013, December 2014, and January 2015. reported in excel files. Article in Journal/Newspaper Antarc* Antarctica Zenodo
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
description This repository provides an"SVM_binary_classification" Jupyter notebook and different data folders fortraining and generalization in a binary classification task using a combination ofsupport vector classifier and Zernike moments. Using a python script in the jupyter notebook and a Zernike momentfile inside eachfolder, one can classify generalizationimages in any two classes among eruption, no-eruption, and non-explosive small events (NESE). It is notable that, the SVM needs to be trained initiallyusing the Zernike moments inside the training data folders. There is also spatial and temporal information on NESEs in December 2013, December 2014, and January 2015. reported in excel files.
format Article in Journal/Newspaper
author Honarbakhsh,Leila
Morra, Gabriele
spellingShingle Honarbakhsh,Leila
Morra, Gabriele
Classification of IR Images of Small Eruptions at the Erebus Volcano, Antarctica, with Zernike moments and Support Vector Machine
author_facet Honarbakhsh,Leila
Morra, Gabriele
author_sort Honarbakhsh,Leila
title Classification of IR Images of Small Eruptions at the Erebus Volcano, Antarctica, with Zernike moments and Support Vector Machine
title_short Classification of IR Images of Small Eruptions at the Erebus Volcano, Antarctica, with Zernike moments and Support Vector Machine
title_full Classification of IR Images of Small Eruptions at the Erebus Volcano, Antarctica, with Zernike moments and Support Vector Machine
title_fullStr Classification of IR Images of Small Eruptions at the Erebus Volcano, Antarctica, with Zernike moments and Support Vector Machine
title_full_unstemmed Classification of IR Images of Small Eruptions at the Erebus Volcano, Antarctica, with Zernike moments and Support Vector Machine
title_sort classification of ir images of small eruptions at the erebus volcano, antarctica, with zernike moments and support vector machine
publisher Zenodo
publishDate 2022
url https://doi.org/10.5281/zenodo.7149379
genre Antarc*
Antarctica
genre_facet Antarc*
Antarctica
op_relation https://doi.org/10.5281/zenodo.7149377
https://doi.org/10.5281/zenodo.7149379
oai:zenodo.org:7149379
op_rights info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.5281/zenodo.714937910.5281/zenodo.7149377
_version_ 1810490498588082176

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