The Astrophysical Journal Letters · 2022 · 14 citations · 18 references
ComputingComputer ScienceEarth SciencesComputer VisionMachine LearningSensor FusionDeep LearningObject RecognitionRemote Sensing Image AnalysisConvolutional Neural Network DetectionConvolutional Neural NetworksDeep Learning DetectionDeep Learning For Fall DetectionDrone ImagingMachine Learning For Fall DetectionRecovery TimeSurface Crusts
Abstract We report the first-time recovery of a fresh meteorite fall using a drone and a machine-learning algorithm. The fireball was observed on 2021 April 1 over Western Australia by the Desert Fireball Network, for which a fall area was calculated for the predicted surviving mass. A search team arrived on-site and surveyed 5.1 km 2 area over a 4 day period. A convolutional neural network, trained on previously recovered meteorites with fusion crusts, processed the images on our field computer after each flight. Meteorite candidates identified by the algorithm were sorted by team members using two user interfaces to eliminate false positives. Surviving candidates were revisited with a smaller drone, and imaged in higher resolution, before being eliminated or finally being visited in person. The 70 g meteorite was recovered within 50 m of the calculated fall line, demonstrating the effectiveness of this methodology, which will facilitate the efficient collection of many more observed meteorite falls.
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Itokawa Dust Particles: A Direct Link Between S-Type Asteroids and Ordinary Chondrites
Tomoki Nakamura, T. Noguchi, Masahiko Tanaka et al. · Science · 2011 · 593 citations
The “European Fireball Network”: Current status and future prospects
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Natural Sciences, Astronomy, Global Navigation Satellite Systems +2