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Title:
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SUNSPOT DETECTION USING DEEP LEARNING TECHNIQUES |
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Author(s):
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Pieter Swanepoel, Günther Richard Drevin, Roelf Du Toit Strauss and Petrus Johannes Steyn |
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ISBN:
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978-989-8704-44-3 |
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Editors:
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Hans Weghorn and Pedro Isaias |
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Year:
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2022 |
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Edition:
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Single |
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Keywords:
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Sunspots, Space Weather, Deep Learning, Object Detection |
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Type:
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Full Paper |
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First Page:
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39 |
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Last Page:
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46 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Accurate and automated monitoring of space weather has become increasingly important in our modern-day world, due to the reliance on critical infrastructure such as wireless communication, power grids, satellite communication, and aviation systems. Solar events such as solar flares and coronal mass ejections can disrupt or damage these system and sunspots are used as markers to determine solar activity through a manual process, thus automated detection and tracking of sunspots form part of the prediction of solar events and prediction of space weather. In this paper the use of deep learning techniques for automated sunspot detection will be investigated. |
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