{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T20:20:50Z","timestamp":1765484450946,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2024,11,15]],"date-time":"2024-11-15T00:00:00Z","timestamp":1731628800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"PNPB Udayana University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The plasmasphere within Earth\u2019s magnetosphere plays a crucial role in space physics, with its electron density distribution being pivotal and strongly influenced by solar activity. Very Low Frequency (VLF) waves, including whistlers, provide valuable insights into this distribution, making the study of their propagation through the plasmasphere essential for predicting space weather impacts on various technologies. In this study, we evaluate the performance of different deep learning model sizes for lightning whistler detection using the YOLO (You Only Look Once) architecture. To achieve this, we transformed the entirety of raw data from the Arase (ERG) Satellite for August 2017 into 2736 images, which were then used to train the models. Our approach involves exposing the models to spectrogram diagrams\u2014visual representations of the frequency content of signals\u2014derived from the Arase Satellite\u2019s WFC (WaveForm Capture) subsystem, with a focus on analyzing whistler-mode plasma waves. We experimented with various model sizes, adjusting epochs, and conducted performance analysis using a partial set of labeled data. The testing phase confirmed the effectiveness of the models, with YOLOv5n emerging as the optimal choice due to its compact size (3.7 MB) and impressive detection speed, making it suitable for resource-constrained applications. Despite challenges such as image quality and the detection of smaller whistlers, YOLOv5n demonstrated commendable accuracy in identifying scenarios with simple shapes, thereby contributing to a deeper understanding of whistlers\u2019 impact on Earth\u2019s magnetosphere and fulfilling the core objectives of this study.<\/jats:p>","DOI":"10.3390\/rs16224264","type":"journal-article","created":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T06:06:54Z","timestamp":1731996414000},"page":"4264","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Deep Learning Model Size Performance Evaluation for Lightning Whistler Detection on Arase Satellite Dataset"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0512-2966","authenticated-orcid":false,"given":"I Made Agus Dwi","family":"Suarjaya","sequence":"first","affiliation":[{"name":"Department of Information Technology, Faculty of Engineering, Udayana University, Bali 80361, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7132-0863","authenticated-orcid":false,"given":"Desy Purnami Singgih","family":"Putri","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Faculty of Engineering, Udayana University, Bali 80361, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9980-3529","authenticated-orcid":false,"given":"Yuji","family":"Tanaka","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Graduate School of Engineering, Kyoto University, Kyoto 606-8501, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9367-1740","authenticated-orcid":false,"given":"Fajar","family":"Purnama","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Faculty of Engineering, Udayana University, Bali 80361, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0638-0756","authenticated-orcid":false,"given":"I Putu Agung","family":"Bayupati","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Faculty of Engineering, Udayana University, Bali 80361, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8303-2822","authenticated-orcid":false,"family":"Linawati","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Faculty of Engineering, Udayana University, Bali 80361, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9304-8235","authenticated-orcid":false,"given":"Yoshiya","family":"Kasahara","sequence":"additional","affiliation":[{"name":"Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa 920-1192, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shoya","family":"Matsuda","sequence":"additional","affiliation":[{"name":"Graduate School of Natural Science and Technology, Kanazawa University, Kanazawa 920-1192, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7998-1240","authenticated-orcid":false,"given":"Yoshizumi","family":"Miyoshi","sequence":"additional","affiliation":[{"name":"Institute for Space\u2013Earth Environmental Research, Nagoya University, Nagoya 464-8601, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2700-0353","authenticated-orcid":false,"given":"Iku","family":"Shinohara","sequence":"additional","affiliation":[{"name":"Institute of Space and Astronautical Science, Yoshinodai, Sagamihara 252-5210, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/S1364-6826(96)00157-5","article-title":"Global electron density distribution in the plasmasphere deduced from Akebono wave data and the IRI model","volume":"59","author":"Kimura","year":"1997","journal-title":"J. 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