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Lightning Storm Detection on Saturn through Machine Learning Analysis of Cassini Dayside Images

Presentation #326.03 in the session Origin and Evolution of Giant Planet Systems II (Poster)

Published onOct 23, 2023
Lightning Storm Detection on Saturn through Machine Learning Analysis of Cassini Dayside Images

From 2004 to 2017, Cassini captured high-resolution images including lightning flashes and also storm clouds on Saturn’s day side. We explore lightning storm clouds’ relationship with Saturn electrical discharges (SED) activity, and use machine learning for detecting lightning storm clouds. This paper introduces an advanced machine learning approach using the YOLOv5 algorithm for automated lightning detection and classification in previously unexplored Saturn images. The model was trained on 230 plus images of the 2010-2011 storm on Saturn’s day side, confirmed to have lightning. Furthermore, the model’s performance was evaluated on images without known lightning storms to assess its generalization capabilities. Another program, Google Cloud Vision API, successfully labeled 2010-2011 storm cloud images as lightning from its default settings without training. Our ongoing efforts aim to refine YOLOv5 algorithm’s performance for smaller lightning storm detection and improve its proficiency in analyzing storm-related phenomena on Saturn.

We will discuss capabilities of machine learning in detecting lightning storms on Saturn

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