Python Code to Train a Neural Network for the Identification of EMIC Wave Events in Spectrograms ...

Python code used to train a convolutional neural network (CNN) for the identification of electromagnetic ion cyclotron (EMIC) wave events in spectrograms. Three versions of the code are provided: one to train and test a model (CNN_Training_zenodo.py), one to test a pre-trained model on new, labeled...

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Bibliographic Details
Main Author: Capman, Nyssa
Format: Software
Language:English
Published: Zenodo 2023
Subjects:
Online Access:https://dx.doi.org/10.5281/zenodo.8280090
https://zenodo.org/record/8280090
id ftdatacite:10.5281/zenodo.8280090
record_format openpolar
spelling ftdatacite:10.5281/zenodo.8280090 2023-10-01T03:51:39+02:00 Python Code to Train a Neural Network for the Identification of EMIC Wave Events in Spectrograms ... Capman, Nyssa 2023 https://dx.doi.org/10.5281/zenodo.8280090 https://zenodo.org/record/8280090 en eng Zenodo https://dx.doi.org/10.5281/zenodo.8280089 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess Space physics Electromagnetic ion cyclotron EMIC waves Spectrograms Software article SoftwareSourceCode 2023 ftdatacite https://doi.org/10.5281/zenodo.828009010.5281/zenodo.8280089 2023-09-04T14:59:05Z Python code used to train a convolutional neural network (CNN) for the identification of electromagnetic ion cyclotron (EMIC) wave events in spectrograms. Three versions of the code are provided: one to train and test a model (CNN_Training_zenodo.py), one to test a pre-trained model on new, labeled test data (CNN_Testing_zenodo.py), and one to test a pre-trained model on new, unlabeled test data (CNN_Classify_zenodo.py). Additionally, pre-labeled spectrograms from the Halley, Antarctica ground magnetometer station between November 2006 and December 2009 are provided, as well as lookup tables to relate pixel locations to time and frequency information in the provided spectrograms. ... Software Antarc* Antarctica DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic Space physics
Electromagnetic ion cyclotron EMIC waves
Spectrograms
spellingShingle Space physics
Electromagnetic ion cyclotron EMIC waves
Spectrograms
Capman, Nyssa
Python Code to Train a Neural Network for the Identification of EMIC Wave Events in Spectrograms ...
topic_facet Space physics
Electromagnetic ion cyclotron EMIC waves
Spectrograms
description Python code used to train a convolutional neural network (CNN) for the identification of electromagnetic ion cyclotron (EMIC) wave events in spectrograms. Three versions of the code are provided: one to train and test a model (CNN_Training_zenodo.py), one to test a pre-trained model on new, labeled test data (CNN_Testing_zenodo.py), and one to test a pre-trained model on new, unlabeled test data (CNN_Classify_zenodo.py). Additionally, pre-labeled spectrograms from the Halley, Antarctica ground magnetometer station between November 2006 and December 2009 are provided, as well as lookup tables to relate pixel locations to time and frequency information in the provided spectrograms. ...
format Software
author Capman, Nyssa
author_facet Capman, Nyssa
author_sort Capman, Nyssa
title Python Code to Train a Neural Network for the Identification of EMIC Wave Events in Spectrograms ...
title_short Python Code to Train a Neural Network for the Identification of EMIC Wave Events in Spectrograms ...
title_full Python Code to Train a Neural Network for the Identification of EMIC Wave Events in Spectrograms ...
title_fullStr Python Code to Train a Neural Network for the Identification of EMIC Wave Events in Spectrograms ...
title_full_unstemmed Python Code to Train a Neural Network for the Identification of EMIC Wave Events in Spectrograms ...
title_sort python code to train a neural network for the identification of emic wave events in spectrograms ...
publisher Zenodo
publishDate 2023
url https://dx.doi.org/10.5281/zenodo.8280090
https://zenodo.org/record/8280090
genre Antarc*
Antarctica
genre_facet Antarc*
Antarctica
op_relation https://dx.doi.org/10.5281/zenodo.8280089
op_rights Open Access
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.5281/zenodo.828009010.5281/zenodo.8280089
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