Machine learning clustering of meteor observations produces a new hardness classification H_class that refines traditional Kb models using more parameters and reveals compositional structure in meteoroid populations.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2roles
dataset 1polarities
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High-speed imaging of four lunar impact flashes reveals lower variance in initial intensity than total energy and no correlation between them, suggesting decoupled vapor and ejecta phases.
citing papers explorer
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A Machine Learning Approach to Meteor Classification
Machine learning clustering of meteor observations produces a new hardness classification H_class that refines traditional Kb models using more parameters and reveals compositional structure in meteoroid populations.
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High-Speed Observations of Lunar Impact Flashes
High-speed imaging of four lunar impact flashes reveals lower variance in initial intensity than total energy and no correlation between them, suggesting decoupled vapor and ejecta phases.