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Abstract:We present a cloud-based tool that uses drones and machine learning to help recover instrumentally observed meteorite falls. We showcase a collection of improvements made upon previous iterations of our system, as well as detail the successes and limitations of this technique when applied to observed meteorite falls in South and Western Australia. This tool is available to the meteoritics research community upon request at this https URL.
| Comments: | 23 pages, 3 figures |
| Subjects: | Earth and Planetary Astrophysics (astro-ph.EP); Instrumentation and Methods for Astrophysics (astro-ph.IM); Machine Learning (cs.LG) |
| Cite as: | arXiv:2605.19179 [astro-ph.EP] |
| (or arXiv:2605.19179v1 [astro-ph.EP] for this version) | |
| https://doi.org/10.48550/arXiv.2605.19179 arXiv-issued DOI via DataCite (pending registration) |
From: Seamus Anderson [view email]
[v1]
Mon, 18 May 2026 23:05:00 UTC (597 KB)
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